Importing Essential Libraries¶

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats
from sklearn.preprocessing import Normalizer
from sklearn.model_selection import train_test_split
import random
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import math

random.seed(25)

Creating a pandas dataframe from the given dataset¶

data= pd.read_csv("energydata_complete.csv")

Checking for Null values¶

data.isnull().any()

date           False
Appliances     False
lights         False
T1             False
RH_1           False
T2             False
RH_2           False
T3             False
RH_3           False
T4             False
RH_4           False
T5             False
RH_5           False
T6             False
RH_6           False
T7             False
RH_7           False
T8             False
RH_8           False
T9             False
RH_9           False
T_out          False
Press_mm_hg    False
RH_out         False
Windspeed      False
Visibility     False
Tdewpoint      False
rv1            False
rv2            False
dtype: bool

data

Stats for all columns¶

data.describe(include='all')

Identifying Correlation¶

plt.figure(figsize=(20,11))
sns.heatmap(data.corr(),annot=True,cmap="BuPu")
plt.show()

data.drop(['date','lights','T9','T6','Visibility','rv1','rv2'],axis=1,inplace=True)

Outlier Detection¶

fig = make_subplots(rows=5, cols=5,subplot_titles=list(data.columns))

a=1
b=1
for i in data.columns:
    fig.append_trace(go.Histogram(x=data[i],name=i,marker_color='#EB89B5'),a, b)
    if b==5:
        b=1
        a+=1
    else : b+=1

fig.show()

fig = go.Figure()
for i in data.columns:
    fig.add_trace(go.Box(x=data[i],name=i,marker_color='lightseagreen'))
fig.show()

data.shape

(19735, 22)

data=data[(np.abs(stats.zscore(data)) < 3.25).all(axis=1)]

data.shape

(18500, 22)

Feature Scaling¶

x=data.iloc[:,1:]
y=data.iloc[:,0]

scaler = Normalizer()
x_scaled = scaler.fit_transform(x)
x_scaled = pd.DataFrame(x_scaled, columns=np.array(x.columns))

Test Train Split : 70% train 30% test¶

x_train, x_test, y_train, y_test = train_test_split(x_scaled, y, test_size=0.3,random_state=85)

x_train.index=list(range(x_train.shape[0]))
x_test.index=list(range(x_test.shape[0]))
y_train.index=list(range(y_train.shape[0]))
y_test.index=list(range(y_test.shape[0]))

x_train.insert(0,'X0',1)
x_test.insert(0,'X0',1)

Functions for Linear and Logistic Regression¶

def y_hat_sum_of_squared(x,betas):
    return x.multiply(betas,axis=1).sum(axis=1)

def cost_sum_of_squared(x,y,betas):
    y_hat=y_hat_sum_of_squared(x,betas)
    Cost_function_value = (((y_hat.subtract(y,axis='rows')).apply(lambda x: x**2)).sum())/(2*(len(y)))
    return Cost_function_value

#def initialize_betas(train,ub,lb):
#    beta=[]
#    for i in range(len(train.columns)):
#        beta.append(random.uniform(ub,lb))
#    return pd.Series(beta,index=train.columns)

def y_hat_sigmoid(x,betas):
    y=x.multiply(betas,axis=1).sum(axis=1)
    y_hat=y.apply(lambda x: 1/(1+math.exp(-x)))
    return y_hat

def cost_sigmoid(x,y,betas):
    y_hat=y_hat_sigmoid(x,betas)
    y_0=y.multiply((y_hat.apply(lambda x: math.log(x))))
    y_1=(y.apply(lambda x: 1-x)).multiply((y_hat.apply(lambda x: math.log(1-x))))
    Cost_function_value = ((y_0.add(y_1)).sum())*(-1/(len(y)))
    return Cost_function_value

def update_betas(flag,x,y,betas,alpha):
    if flag=='lr':
        y_hat=y_hat_sum_of_squared(x,betas)
    elif flag=='lgr':
        y_hat=y_hat_sigmoid(x,betas)
    new_betas=betas.subtract((((x.multiply(y_hat.subtract(y,axis='rows'),axis=0)).sum())/len(y))*alpha,axis='rows')
    return new_betas

def batch_gradient_descent_v3(flag,x_train,y_train,x_test,y_test,alpha,criteria,max_runs):
    #### Initialize betas
    betas=pd.Series(0,index=x_train.columns)
    initial_beta=betas
        
    ### In function variables
    graph=pd.DataFrame(columns=['Cost_train','Cost_test','Iteration','Alpha','Convergence_criteria','Accuracy'])
    a=0
    
    if flag=='lr':
              
        for i in range(max_runs):
            ## Training Cost Calculation
            cost_train=cost_sum_of_squared(x_train,y_train,betas)
            
            ## Test Cost Calculation
            cost_test=cost_sum_of_squared(x_test,y_test,betas)
            
            #### Appending data graph variable
            graph=graph.append({'Cost_train':cost_train,'Cost_test':cost_test,'Iteration':a+1,
                                'Alpha':alpha,'Convergence_criteria':criteria,'Accuracy':0},ignore_index=True)
            
            ## Update Rule
            betas=update_betas(flag,x_train,y_train,betas,alpha)
            
            a+=1
            print("Iteration : ",a," Cost train: ",graph['Cost_train'].iloc[-1]," Cost test: ",graph['Cost_test'].iloc[-1])
            if a>1:
                if(graph['Cost_train'].iloc[-2]-graph['Cost_train'].iloc[-1])<0:
                    print('Cost Function Increasing with iteration')
                    print('Alpha value too large')
                    break
                elif(graph['Cost_train'].iloc[-2]-graph['Cost_train'].iloc[-1])<=criteria :
                    print('Convergence Achieved at ',graph['Iteration'].iloc[-1],' iteration')
                    print('Cost Minima Found : ',graph['Cost_train'].iloc[-1])
                    print('Betas : ')
                    print(betas)
                    break
            else: continue
    
    elif flag=='lgr':
               
        for i in range(max_runs):
            ## Training Cost Calculation
            cost_train=cost_sigmoid(x_train,y_train,betas)
            
            ## Test Cost Calculation
            cost_test=cost_sigmoid(x_test,y_test,betas)
            
            ## Accuracy test
            result=pd.concat([y_test,y_hat_sigmoid(x_test,betas).apply(lambda x: 0 if x<0.5 else 1)],axis=1) ## Alpha=4
            result['prediction']=np.where(result['Appliances']==result[0],'good','bad')
            Correct_pred=result[result['prediction']=='good']['prediction'].count()
            Total_pred=result.shape[0]
            Acc=Correct_pred/Total_pred
                      
            #### Appending data graph variable
            graph=graph.append({'Cost_train':cost_train,'Cost_test':cost_test,'Iteration':a+1,
                                'Alpha':alpha,'Convergence_criteria':criteria,'Accuracy':Acc},
                               ignore_index=True)
            
            ## Update Rule
            betas=update_betas(flag,x_train,y_train,betas,alpha)
            
            a+=1
            print("Iteration : ",a," Cost train: ",graph['Cost_train'].iloc[-1]," Cost test: ",
                  graph['Cost_test'].iloc[-1]," Accuracy: ",graph['Accuracy'].iloc[-1])
            if a>1:
                if(graph['Cost_train'].iloc[-2]-graph['Cost_train'].iloc[-1])<=0:
                    print('Cost Function Increasing with iteration')
                    print('Alpha value too large')
                    break
                #elif(graph['Cost_train'].iloc[-2]-graph['Cost_train'].iloc[-1])<=criteria :
                #    print('Convergence Achieved at ',graph['Iteration'].iloc[-1],' iteration')
                #    print('Cost Minima Found : ',graph['Cost_train'].iloc[-1])
                #    print('Betas : ')
                #    print(betas)
                #    break
            else: continue
    return initial_beta,betas,graph

Linear Regression with Initial input Parameters¶

initial_params,params,graph=batch_gradient_descent_v3('lr',x_train,y_train,x_test,y_test,0.01,0.01,100000)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6004.921595392998  Cost test:  6146.140784354759
Iteration :  3  Cost train:  5866.6459199546825  Cost test:  6006.525970946973
Iteration :  4  Cost train:  5733.8396173644505  Cost test:  5872.407245918736
Iteration :  5  Cost train:  5606.286349003106  Cost test:  5743.56773832182
Iteration :  6  Cost train:  5483.778333429736  Cost test:  5619.799144966726
Iteration :  7  Cost train:  5366.116007906323  Cost test:  5500.901391738041
Iteration :  8  Cost train:  5253.107703310571  Cost test:  5386.682308302158
Iteration :  9  Cost train:  5144.569331907452  Cost test:  5276.957315677658
Iteration :  10  Cost train:  5040.324087470774  Cost test:  5171.549126159725
Iteration :  11  Cost train:  4940.202157266335  Cost test:  5070.287455109965
Iteration :  12  Cost train:  4844.040445427434  Cost test:  4973.008744142392
Iteration :  13  Cost train:  4751.682307272158  Cost test:  4879.555895254906
Iteration :  14  Cost train:  4662.977294129624  Cost test:  4789.7780154733655
Iteration :  15  Cost train:  4577.780908259506  Cost test:  4703.530171592525
Iteration :  16  Cost train:  4495.954367465604  Cost test:  4620.673154614529
Iteration :  17  Cost train:  4417.364379020042  Cost test:  4541.073253501451
Iteration :  18  Cost train:  4341.8829225297695  Cost test:  4464.602037873537
Iteration :  19  Cost train:  4269.387041391689  Cost test:  4391.136149299365
Iteration :  20  Cost train:  4199.758642496697  Cost test:  4320.557100838167
Iteration :  21  Cost train:  4132.884303856324  Cost test:  4252.751084507926
Iteration :  22  Cost train:  4068.6550898386313  Cost test:  4187.608786365859
Iteration :  23  Cost train:  4006.966373712364  Cost test:  4125.025208900202
Iteration :  24  Cost train:  3947.717667210289  Cost test:  4064.8995004441986
Iteration :  25  Cost train:  3890.8124568340877  Cost test:  4007.134791334559
Iteration :  26  Cost train:  3836.1580466341297  Cost test:  3951.6380365477057
Iteration :  27  Cost train:  3783.665407208026  Cost test:  3898.3198645576217
Iteration :  28  Cost train:  3733.249030671973  Cost test:  3847.0944321692555
Iteration :  29  Cost train:  3684.826791368649  Cost test:  3797.8792850912046
Iteration :  30  Cost train:  3638.3198120847424  Cost test:  3750.595224020697
Iteration :  31  Cost train:  3593.652335560183  Cost test:  3705.1661760228926
Iteration :  32  Cost train:  3550.7516010797776  Cost test:  3661.519070995141
Iteration :  33  Cost train:  3509.5477259462036  Cost test:  3619.5837230151287
Iteration :  34  Cost train:  3469.9735916412856  Cost test:  3579.2927163797576
Iteration :  35  Cost train:  3431.9647344901123  Cost test:  3540.5812961492934
Iteration :  36  Cost train:  3395.45924064989  Cost test:  3503.3872630186083
Iteration :  37  Cost train:  3360.3976452524594  Cost test:  3467.6508723444235
Iteration :  38  Cost train:  3326.722835536189  Cost test:  3433.314737164195
Iteration :  39  Cost train:  3294.3799578094436  Cost test:  3400.323735048811
Iteration :  40  Cost train:  3263.316328094071  Cost test:  3368.624918637502
Iteration :  41  Cost train:  3233.4813463033447  Cost test:  3338.1674297093473
Iteration :  42  Cost train:  3204.8264138145623  Cost test:  3308.9024166515455
Iteration :  43  Cost train:  3177.304854302024  Cost test:  3280.7829551901277
Iteration :  44  Cost train:  3150.871837701421  Cost test:  3253.7639722541066
Iteration :  45  Cost train:  3125.484307181789  Cost test:  3227.8021728491676
Iteration :  46  Cost train:  3101.1009090060456  Cost test:  3202.855969821898
Iteration :  47  Cost train:  3077.6819251658667  Cost test:  3178.885416400252
Iteration :  48  Cost train:  3055.18920868116  Cost test:  3155.8521414004886
Iteration :  49  Cost train:  3033.5861214587376  Cost test:  3133.7192869951423
Iteration :  50  Cost train:  3012.8374746089644  Cost test:  3112.4514489407575
Iteration :  51  Cost train:  2992.909471123154  Cost test:  3092.0146191681406
Iteration :  52  Cost train:  2973.76965081833  Cost test:  3072.3761306417014
Iteration :  53  Cost train:  2955.386837459682  Cost test:  3053.504604398179
Iteration :  54  Cost train:  2937.731087974561  Cost test:  3035.369898678569
Iteration :  55  Cost train:  2920.773643675298  Cost test:  3017.943060070506
Iteration :  56  Cost train:  2904.48688341138  Cost test:  3001.1962765815842
Iteration :  57  Cost train:  2888.8442785746706  Cost test:  2985.102832567303
Iteration :  58  Cost train:  2873.820349884382  Cost test:  2969.6370654402835
Iteration :  59  Cost train:  2859.390625881394  Cost test:  2954.774324090342
Iteration :  60  Cost train:  2845.531603064316  Cost test:  2940.4909289477773
Iteration :  61  Cost train:  2832.220707602349  Cost test:  2926.7641336248967
Iteration :  62  Cost train:  2819.436258562573  Cost test:  2913.572088073395
Iteration :  63  Cost train:  2807.157432591769  Cost test:  2900.8938031976477
Iteration :  64  Cost train:  2795.3642299952344  Cost test:  2888.7091168663505
Iteration :  65  Cost train:  2784.037442157336  Cost test:  2876.9986612672437
Iteration :  66  Cost train:  2773.1586202507224  Cost test:  2865.743831551801
Iteration :  67  Cost train:  2762.71004518324  Cost test:  2854.926755718893
Iteration :  68  Cost train:  2752.6746987335814  Cost test:  2844.5302656884446
Iteration :  69  Cost train:  2743.0362358286443  Cost test:  2834.5378695180407
Iteration :  70  Cost train:  2733.7789579174555  Cost test:  2824.9337247172944
Iteration :  71  Cost train:  2724.8877873982747  Cost test:  2815.7026126165824
Iteration :  72  Cost train:  2716.348243057222  Cost test:  2806.8299137484623
Iteration :  73  Cost train:  2708.1464164784193  Cost test:  2798.3015842017426
Iteration :  74  Cost train:  2700.2689493872194  Cost test:  2790.1041329097534
Iteration :  75  Cost train:  2692.703011889614  Cost test:  2782.2245998358876
Iteration :  76  Cost train:  2685.4362815723707  Cost test:  2774.650535020942
Iteration :  77  Cost train:  2678.4569234298565  Cost test:  2767.3699784581954
Iteration :  78  Cost train:  2671.7535705848445  Cost test:  2760.3714407635002
Iteration :  79  Cost train:  2665.3153057719037  Cost test:  2753.643884608958
Iteration :  80  Cost train:  2659.1316435532035  Cost test:  2747.17670689001
Iteration :  81  Cost train:  2653.1925132377614  Cost test:  2740.959721596929
Iteration :  82  Cost train:  2647.488242476319  Cost test:  2734.983143362893
Iteration :  83  Cost train:  2642.009541505109  Cost test:  2729.237571661886
Iteration :  84  Cost train:  2636.7474880128575  Cost test:  2723.7139756307342
Iteration :  85  Cost train:  2631.69351260636  Cost test:  2718.4036794906256
Iteration :  86  Cost train:  2626.839384850966  Cost test:  2713.2983485444033
Iteration :  87  Cost train:  2622.1771998632244  Cost test:  2708.389975726879
Iteration :  88  Cost train:  2617.699365433848  Cost test:  2703.670868686319
Iteration :  89  Cost train:  2613.398589660024  Cost test:  2699.133637376089
Iteration :  90  Cost train:  2609.2678690669286  Cost test:  2694.7711821363196
Iteration :  91  Cost train:  2605.300477199083  Cost test:  2690.576682246201
Iteration :  92  Cost train:  2601.489953662975  Cost test:  2686.543584928328
Iteration :  93  Cost train:  2597.8300936030996  Cost test:  2682.665594787219
Iteration :  94  Cost train:  2594.31493759426  Cost test:  2678.9366636648474
Iteration :  95  Cost train:  2590.9387619336862  Cost test:  2675.3509808967187
Iteration :  96  Cost train:  2587.6960693171372  Cost test:  2671.902963952649
Iteration :  97  Cost train:  2584.5815798838057  Cost test:  2668.5872494470545
Iteration :  98  Cost train:  2581.5902226154412  Cost test:  2665.3986845041427
Iteration :  99  Cost train:  2578.7171270756735  Cost test:  2662.3323184639844
Iteration :  100  Cost train:  2575.957615476088  Cost test:  2659.3833949159903
Iteration :  101  Cost train:  2573.3071950561175  Cost test:  2656.547344046871
Iteration :  102  Cost train:  2570.7615507643513  Cost test:  2653.819775290629
Iteration :  103  Cost train:  2568.316538229325  Cost test:  2651.1964702686746
Iteration :  104  Cost train:  2565.9681770083535  Cost test:  2648.673376008581
Iteration :  105  Cost train:  2563.712644103398  Cost test:  2646.2465984304827
Iteration :  106  Cost train:  2561.546267733415  Cost test:  2643.9123960905363
Iteration :  107  Cost train:  2559.4655213530336  Cost test:  2641.667174171291
Iteration :  108  Cost train:  2557.4670179078253  Cost test:  2639.507478709208
Iteration :  109  Cost train:  2555.547504316797  Cost test:  2637.4299910499662
Iteration :  110  Cost train:  2553.7038561731356  Cost test:  2635.431522522551
Iteration :  111  Cost train:  2551.933072654555  Cost test:  2633.509009323483
Iteration :  112  Cost train:  2550.2322716349654  Cost test:  2631.659507602889
Iteration :  113  Cost train:  2548.5986849894994  Cost test:  2629.880188744436
Iteration :  114  Cost train:  2547.0296540852414  Cost test:  2628.168334831474
Iteration :  115  Cost train:  2545.522625450325  Cost test:  2626.521334292032
Iteration :  116  Cost train:  2544.075146614332  Cost test:  2624.9366777155997
Iteration :  117  Cost train:  2542.684862113225  Cost test:  2623.4119538349114
Iteration :  118  Cost train:  2541.3495096523043  Cost test:  2621.944845666215
Iteration :  119  Cost train:  2540.0669164209344  Cost test:  2620.533126801767
Iteration :  120  Cost train:  2538.834995553043  Cost test:  2619.174657848539
Iteration :  121  Cost train:  2537.6517427276217  Cost test:  2617.867383007358
Iteration :  122  Cost train:  2536.5152329036896  Cost test:  2616.609326786948
Iteration :  123  Cost train:  2535.4236171844123  Cost test:  2615.398590847524
Iteration :  124  Cost train:  2534.3751198052487  Cost test:  2614.2333509688433
Iteration :  125  Cost train:  2533.3680352412375  Cost test:  2613.111854137787
Iteration :  126  Cost train:  2532.4007254287053  Cost test:  2612.03241575075
Iteration :  127  Cost train:  2531.4716170968577  Cost test:  2610.9934169263147
Iteration :  128  Cost train:  2530.5791992049317  Cost test:  2609.9933019238542
Iteration :  129  Cost train:  2529.722020480714  Cost test:  2609.0305756638654
Iteration :  130  Cost train:  2528.8986870564177  Cost test:  2608.103801346039
Iteration :  131  Cost train:  2528.1078601980807  Cost test:  2607.2115981611882
Iteration :  132  Cost train:  2527.348254124771  Cost test:  2606.3526390933507
Iteration :  133  Cost train:  2526.61863391405  Cost test:  2605.5256488084733
Iteration :  134  Cost train:  2525.9178134902904  Cost test:  2604.7294016262963
Iteration :  135  Cost train:  2525.24465369256  Cost test:  2603.9627195721328
Iteration :  136  Cost train:  2524.5980604189335  Cost test:  2603.2244705053845
Iteration :  137  Cost train:  2523.976982844204  Cost test:  2602.513566321786
Iteration :  138  Cost train:  2523.3804117080876  Cost test:  2601.8289612264484
Iteration :  139  Cost train:  2522.8073776711453  Cost test:  2601.169650074913
Iteration :  140  Cost train:  2522.256949735731  Cost test:  2600.534666779539
Iteration :  141  Cost train:  2521.7282337293973  Cost test:  2599.9230827786323
Iteration :  142  Cost train:  2521.2203708482916  Cost test:  2599.3340055658578
Iteration :  143  Cost train:  2520.7325362581682  Cost test:  2598.766577277534
Iteration :  144  Cost train:  2520.263937750734  Cost test:  2598.2199733355446
Iteration :  145  Cost train:  2519.8138144531445  Cost test:  2597.693401143668
Iteration :  146  Cost train:  2519.381435588544  Cost test:  2597.1860988352073
Iteration :  147  Cost train:  2518.9660992856293  Cost test:  2596.697334069911
Iteration :  148  Cost train:  2518.5671314353094  Cost test:  2596.2264028782292
Iteration :  149  Cost train:  2518.183884592577  Cost test:  2595.772628551043
Iteration :  150  Cost train:  2517.815736921827  Cost test:  2595.3353605730745
Iteration :  151  Cost train:  2517.462091183885  Cost test:  2594.913973598244
Iteration :  152  Cost train:  2517.122373763108  Cost test:  2594.5078664653383
Iteration :  153  Cost train:  2516.7960337329655  Cost test:  2594.1164612523835
Iteration :  154  Cost train:  2516.482541958583  Cost test:  2593.739202368201
Iteration :  155  Cost train:  2516.18139023478  Cost test:  2593.375555679687
Iteration :  156  Cost train:  2515.892090458208  Cost test:  2593.025007673393
Iteration :  157  Cost train:  2515.614173832229  Cost test:  2592.6870646500715
Iteration :  158  Cost train:  2515.34719010325  Cost test:  2592.3612519508724
Iteration :  159  Cost train:  2515.0907068272586  Cost test:  2592.0471132139514
Iteration :  160  Cost train:  2514.8443086653733  Cost test:  2591.744209660286
Iteration :  161  Cost train:  2514.6075967072584  Cost test:  2591.4521194075496
Iteration :  162  Cost train:  2514.3801878213003  Cost test:  2591.170436810947
Iteration :  163  Cost train:  2514.1617140304866  Cost test:  2590.8987718299218
Iteration :  164  Cost train:  2513.9518219129714  Cost test:  2590.6367494197534
Iteration :  165  Cost train:  2513.7501720263544  Cost test:  2590.3840089470277
Iteration :  166  Cost train:  2513.5564383547294  Cost test:  2590.140203628069
Iteration :  167  Cost train:  2513.370307777604  Cost test:  2589.904999989403
Iteration :  168  Cost train:  2513.191479559829  Cost test:  2589.678077349408
Iteration :  169  Cost train:  2513.0196648617  Cost test:  2589.4591273202927
Iteration :  170  Cost train:  2512.8545862684396  Cost test:  2589.24785332963
Iteration :  171  Cost train:  2512.695977338289  Cost test:  2589.0439701606456
Iteration :  172  Cost train:  2512.543582168475  Cost test:  2588.8472035105488
Iteration :  173  Cost train:  2512.3971549783455  Cost test:  2588.6572895661757
Iteration :  174  Cost train:  2512.2564597089927  Cost test:  2588.4739745962756
Iteration :  175  Cost train:  2512.1212696387142  Cost test:  2588.29701455978
Iteration :  176  Cost train:  2511.9913670136852  Cost test:  2588.1261747294225
Iteration :  177  Cost train:  2511.8665426932357  Cost test:  2587.961229330112
Iteration :  178  Cost train:  2511.746595809162  Cost test:  2587.801961191472
Iteration :  179  Cost train:  2511.6313334385154  Cost test:  2587.6481614139907
Iteration :  180  Cost train:  2511.5205702893263  Cost test:  2587.499629048251
Iteration :  181  Cost train:  2511.4141283987688  Cost test:  2587.356170786712
Iteration :  182  Cost train:  2511.3118368432556  Cost test:  2587.2176006675677
Iteration :  183  Cost train:  2511.213531460008  Cost test:  2587.0837397901887
Iteration :  184  Cost train:  2511.1190545796335  Cost test:  2586.9544160417045
Iteration :  185  Cost train:  2511.0282547692805  Cost test:  2586.8294638342795
Iteration :  186  Cost train:  2510.940986585959  Cost test:  2586.7087238526706
Iteration :  187  Cost train:  2510.8571103396093  Cost test:  2586.5920428116515
Iteration :  188  Cost train:  2510.776491865553  Cost test:  2586.4792732229266
Iteration :  189  Cost train:  2510.6990023059348  Cost test:  2586.370273171153
Iteration :  190  Cost train:  2510.6245178998142  Cost test:  2586.2649060987137
Iteration :  191  Cost train:  2510.5529197815604  Cost test:  2586.1630405989076
Iteration :  192  Cost train:  2510.48409378722  Cost test:  2586.064550217209
Iteration :  193  Cost train:  2510.4179302685434  Cost test:  2585.969313260294
Iteration :  194  Cost train:  2510.3543239143705  Cost test:  2585.877212612517
Iteration :  195  Cost train:  2510.2931735790758  Cost test:  2585.788135559559
Iteration :  196  Cost train:  2510.2343821178056  Cost test:  2585.7019736189504
Iteration :  197  Cost train:  2510.177856228226  Cost test:  2585.6186223772047
Iteration :  198  Cost train:  2510.123506298537  Cost test:  2585.53798133331
Iteration :  199  Cost train:  2510.0712462614924  Cost test:  2585.459953748317
Iteration :  200  Cost train:  2510.0209934542004  Cost test:  2585.3844465007905
Iteration :  201  Cost train:  2509.97266848346  Cost test:  2585.3113699478968
Iteration :  202  Cost train:  2509.9261950964337  Cost test:  2585.2406377918987
Iteration :  203  Cost train:  2509.8815000564323  Cost test:  2585.1721669518497
Iteration :  204  Cost train:  2509.8385130236115  Cost test:  2585.105877440287
Iteration :  205  Cost train:  2509.797166440387  Cost test:  2585.0416922447166
Iteration :  206  Cost train:  2509.7573954213863  Cost test:  2584.9795372137173
Iteration :  207  Cost train:  2509.7191376477467  Cost test:  2584.919340947467
Iteration :  208  Cost train:  2509.682333265603  Cost test:  2584.8610346925325
Iteration :  209  Cost train:  2509.646924788582  Cost test:  2584.80455224074
Iteration :  210  Cost train:  2509.6128570041574  Cost test:  2584.749829831984
Iteration :  211  Cost train:  2509.580076883712  Cost test:  2584.6968060608015
Iteration :  212  Cost train:  2509.548533496151  Cost test:  2584.645421786585
Iteration :  213  Cost train:  2509.5181779249347  Cost test:  2584.595620047266
Iteration :  214  Cost train:  2509.4889631883984  Cost test:  2584.547345976361
Iteration :  215  Cost train:  2509.4608441632145  Cost test:  2584.500546723225
Iteration :  216  Cost train:  2509.4337775108893  Cost test:  2584.4551713764017
Iteration :  217  Cost train:  2509.407721607163  Cost test:  2584.41117088994
Iteration :  218  Cost train:  2509.3826364742063  Cost test:  2584.36849801257
Iteration :  219  Cost train:  2509.358483715494  Cost test:  2584.327107219615
Iteration :  220  Cost train:  2509.3352264532587  Cost test:  2584.286954647543
Iteration :  221  Cost train:  2509.312829268417  Cost test:  2584.247998031049
Iteration :  222  Cost train:  2509.291258142871  Cost test:  2584.2101966425694
Iteration :  223  Cost train:  2509.2704804040945  Cost test:  2584.173511234137
Iteration :  224  Cost train:  2509.250464671907  Cost test:  2584.137903981477
Iteration :  225  Cost train:  2509.231180807359  Cost test:  2584.1033384302686
Iteration :  226  Cost train:  2509.2125998636325  Cost test:  2584.0697794444773
Iteration :  227  Cost train:  2509.194694038888  Cost test:  2584.037193156676
Iteration :  228  Cost train:  2509.1774366309755  Cost test:  2584.0055469202953
Iteration :  229  Cost train:  2509.160801993937  Cost test:  2583.9748092636964
Iteration :  230  Cost train:  2509.1447654962294  Cost test:  2583.944949846028
Iteration :  231  Cost train:  2509.129303480597  Cost test:  2583.9159394147755
Iteration :  232  Cost train:  2509.1143932255395  Cost test:  2583.887749764944
Iteration :  233  Cost train:  2509.1000129082936  Cost test:  2583.8603536998153
Iteration :  234  Cost train:  2509.0861415692843  Cost test:  2583.8337249932074
Iteration :  235  Cost train:  2509.0727590779875  Cost test:  2583.8078383531893
Iteration :  236  Cost train:  2509.0598461001287  Cost test:  2583.7826693871884
Iteration :  237  Cost train:  2509.047384066194  Cost test:  2583.758194568432
Iteration :  238  Cost train:  2509.0353551411777  Cost test:  2583.73439120368
Iteration :  239  Cost train:  2509.0237421955308  Cost test:  2583.711237402198
Iteration :  240  Cost train:  2509.0125287772544  Cost test:  2583.6887120459087
Iteration :  241  Cost train:  2509.0016990851027  Cost test:  2583.6667947606966
Iteration :  242  Cost train:  2508.9912379428406  Cost test:  2583.6454658888033
Iteration :  243  Cost train:  2508.9811307745204  Cost test:  2583.6247064622826
Iteration :  244  Cost train:  2508.9713635807425  Cost test:  2583.6044981774653
Convergence Achieved at  244.0  iteration
Cost Minima Found :  2508.9713635807425
Betas : 
X0             42.409463
T1              1.216730
RH_1            2.266395
T2              1.177598
RH_2            2.156583
T3              1.262312
RH_3            2.168333
T4              1.171987
RH_4            2.138609
T5              1.086625
RH_5            2.711602
RH_6            2.322392
T7              1.133409
RH_7            1.853996
T8              1.239049
RH_8            2.206655
RH_9            2.208502
T_out           0.534300
Press_mm_hg    41.517579
RH_out          3.816893
Windspeed       0.268481
Tdewpoint       0.217483
dtype: float64

Plot Cost Vs Iteration with initial input parameter¶

fig=go.Figure()
fig.add_trace(go.Scatter(y=graph['Cost_train'],
                         x=graph['Iteration'],
                         mode='lines',
                         name='Train'))
fig.add_trace(go.Scatter(y=graph['Cost_test'],
                         x=graph['Iteration'],
                         mode='lines',
                         name='Test'))
fig.update_layout(title='Cost Vs Iteration',
                   xaxis_title='Iteration',
                   yaxis_title='Cost')
fig.show()

Determine best Alpha(Experiment 1)¶

x=[0.001,0.003,0.005,0.01,0.05,0.5,1]
minima=pd.DataFrame(columns=['Alpha','Cost_test','Iteration'])
for i in x:
    initial_params,params,graph=batch_gradient_descent_v3('lr',x_train,y_train,x_test,y_test,i,0.01,100000)
    minima=minima.append(graph[['Alpha','Cost_test','Iteration']],ignore_index=True)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6134.364134792519  Cost test:  6276.8130823934025
Iteration :  3  Cost train:  6119.894362772303  Cost test:  6262.206944961773
Iteration :  4  Cost train:  6105.482344391204  Cost test:  6247.658833199511
Iteration :  5  Cost train:  6091.127849132951  Cost test:  6233.168516048373
Iteration :  6  Cost train:  6076.830647401346  Cost test:  6218.735763371273
Iteration :  7  Cost train:  6062.590510516595  Cost test:  6204.360345948607
Iteration :  8  Cost train:  6048.407210711653  Cost test:  6190.042035474587
Iteration :  9  Cost train:  6034.280521128573  Cost test:  6175.780604553596
Iteration :  10  Cost train:  6020.210215814887  Cost test:  6161.575826696563
Iteration :  11  Cost train:  6006.196069719985  Cost test:  6147.427476317343
Iteration :  12  Cost train:  5992.237858691518  Cost test:  6133.335328729115
Iteration :  13  Cost train:  5978.3353594718155  Cost test:  6119.299160140798
Iteration :  14  Cost train:  5964.488349694307  Cost test:  6105.318747653472
Iteration :  15  Cost train:  5950.696607879973  Cost test:  6091.393869256827
Iteration :  16  Cost train:  5936.959913433797  Cost test:  6077.524303825608
Iteration :  17  Cost train:  5923.278046641241  Cost test:  6063.7098311160935
Iteration :  18  Cost train:  5909.65078866473  Cost test:  6049.950231762579
Iteration :  19  Cost train:  5896.077921540145  Cost test:  6036.245287273869
Iteration :  20  Cost train:  5882.559228173354  Cost test:  6022.594780029787
Iteration :  21  Cost train:  5869.0944923367215  Cost test:  6008.998493277715
Iteration :  22  Cost train:  5855.683498665657  Cost test:  5995.456211129115
Iteration :  23  Cost train:  5842.32603265517  Cost test:  5981.967718556097
Iteration :  24  Cost train:  5829.021880656442  Cost test:  5968.532801387972
Iteration :  25  Cost train:  5815.770829873406  Cost test:  5955.151246307844
Iteration :  26  Cost train:  5802.572668359342  Cost test:  5941.822840849204
Iteration :  27  Cost train:  5789.427185013487  Cost test:  5928.547373392528
Iteration :  28  Cost train:  5776.3341695776635  Cost test:  5915.32463316191
Iteration :  29  Cost train:  5763.29341263291  Cost test:  5902.154410221686
Iteration :  30  Cost train:  5750.304705596133  Cost test:  5889.036495473092
Iteration :  31  Cost train:  5737.367840716775  Cost test:  5875.970680650921
Iteration :  32  Cost train:  5724.4826110734875  Cost test:  5862.956758320199
Iteration :  33  Cost train:  5711.64881057082  Cost test:  5849.994521872871
Iteration :  34  Cost train:  5698.866233935927  Cost test:  5837.083765524506
Iteration :  35  Cost train:  5686.134676715285  Cost test:  5824.224284311011
Iteration :  36  Cost train:  5673.453935271416  Cost test:  5811.415874085355
Iteration :  37  Cost train:  5660.823806779641  Cost test:  5798.658331514316
Iteration :  38  Cost train:  5648.244089224825  Cost test:  5785.951454075229
Iteration :  39  Cost train:  5635.714581398155  Cost test:  5773.295040052758
Iteration :  40  Cost train:  5623.235082893912  Cost test:  5760.68888853567
Iteration :  41  Cost train:  5610.8053941062735  Cost test:  5748.132799413633
Iteration :  42  Cost train:  5598.425316226118  Cost test:  5735.626573374017
Iteration :  43  Cost train:  5586.0946512378505  Cost test:  5723.170011898718
Iteration :  44  Cost train:  5573.813201916218  Cost test:  5710.762917260979
Iteration :  45  Cost train:  5561.580771823178  Cost test:  5698.405092522244
Iteration :  46  Cost train:  5549.39716530474  Cost test:  5686.096341529005
Iteration :  47  Cost train:  5537.2621874878405  Cost test:  5673.836468909681
Iteration :  48  Cost train:  5525.175644277233  Cost test:  5661.6252800714865
Iteration :  49  Cost train:  5513.137342352372  Cost test:  5649.462581197335
Iteration :  50  Cost train:  5501.147089164326  Cost test:  5637.34817924274
Iteration :  51  Cost train:  5489.204692932701  Cost test:  5625.281881932735
Iteration :  52  Cost train:  5477.309962642568  Cost test:  5613.263497758804
Iteration :  53  Cost train:  5465.462708041411  Cost test:  5601.2928359758225
Iteration :  54  Cost train:  5453.662739636082  Cost test:  5589.369706599017
Iteration :  55  Cost train:  5441.9098686897705  Cost test:  5577.493920400924
Iteration :  56  Cost train:  5430.2039072189855  Cost test:  5565.66528890838
Iteration :  57  Cost train:  5418.544667990544  Cost test:  5553.883624399503
Iteration :  58  Cost train:  5406.93196451859  Cost test:  5542.1487399007
Iteration :  59  Cost train:  5395.365611061592  Cost test:  5530.460449183683
Iteration :  60  Cost train:  5383.845422619388  Cost test:  5518.8185667624975
Iteration :  61  Cost train:  5372.371214930215  Cost test:  5507.222907890555
Iteration :  62  Cost train:  5360.942804467774  Cost test:  5495.673288557691
Iteration :  63  Cost train:  5349.560008438285  Cost test:  5484.169525487226
Iteration :  64  Cost train:  5338.222644777564  Cost test:  5472.711436133034
Iteration :  65  Cost train:  5326.930532148116  Cost test:  5461.298838676637
Iteration :  66  Cost train:  5315.683489936229  Cost test:  5449.931552024297
Iteration :  67  Cost train:  5304.481338249088  Cost test:  5438.609395804127
Iteration :  68  Cost train:  5293.3238979119  Cost test:  5427.332190363216
Iteration :  69  Cost train:  5282.2109904650215  Cost test:  5416.099756764746
Iteration :  70  Cost train:  5271.14243816111  Cost test:  5404.911916785161
Iteration :  71  Cost train:  5260.118063962278  Cost test:  5393.768492911296
Iteration :  72  Cost train:  5249.137691537264  Cost test:  5382.6693083375585
Iteration :  73  Cost train:  5238.201145258606  Cost test:  5371.6141869631065
Iteration :  74  Cost train:  5227.308250199841  Cost test:  5360.60295338903
Iteration :  75  Cost train:  5216.458832132701  Cost test:  5349.635432915555
Iteration :  76  Cost train:  5205.652717524326  Cost test:  5338.711451539256
Iteration :  77  Cost train:  5194.8897335344955  Cost test:  5327.830835950279
Iteration :  78  Cost train:  5184.169708012852  Cost test:  5316.993413529569
Iteration :  79  Cost train:  5173.492469496159  Cost test:  5306.199012346125
Iteration :  80  Cost train:  5162.8578472055515  Cost test:  5295.447461154244
Iteration :  81  Cost train:  5152.265671043808  Cost test:  5284.738589390796
Iteration :  82  Cost train:  5141.715771592625  Cost test:  5274.0722271725
Iteration :  83  Cost train:  5131.207980109914  Cost test:  5263.448205293208
Iteration :  84  Cost train:  5120.742128527098  Cost test:  5252.866355221211
Iteration :  85  Cost train:  5110.318049446427  Cost test:  5242.3265090965415
Iteration :  86  Cost train:  5099.935576138289  Cost test:  5231.8284997283
Iteration :  87  Cost train:  5089.594542538564  Cost test:  5221.3721605919845
Iteration :  88  Cost train:  5079.294783245944  Cost test:  5210.957325826831
Iteration :  89  Cost train:  5069.036133519308  Cost test:  5200.583830233168
Iteration :  90  Cost train:  5058.818429275076  Cost test:  5190.251509269778
Iteration :  91  Cost train:  5048.6415070845815  Cost test:  5179.960199051274
Iteration :  92  Cost train:  5038.505204171471  Cost test:  5169.70973634548
Iteration :  93  Cost train:  5028.409358409084  Cost test:  5159.49995857083
Iteration :  94  Cost train:  5018.353808317874  Cost test:  5149.330703793768
Iteration :  95  Cost train:  5008.338393062817  Cost test:  5139.201810726167
Iteration :  96  Cost train:  4998.362952450841  Cost test:  5129.113118722755
Iteration :  97  Cost train:  4988.427326928264  Cost test:  5119.064467778544
Iteration :  98  Cost train:  4978.531357578245  Cost test:  5109.055698526289
Iteration :  99  Cost train:  4968.674886118235  Cost test:  5099.086652233932
Iteration :  100  Cost train:  4958.857754897453  Cost test:  5089.1571708020765
Iteration :  101  Cost train:  4949.0798068943595  Cost test:  5079.267096761459
Iteration :  102  Cost train:  4939.340885714147  Cost test:  5069.416273270437
Iteration :  103  Cost train:  4929.640835586237  Cost test:  5059.604544112491
Iteration :  104  Cost train:  4919.9795013617895  Cost test:  5049.831753693722
Iteration :  105  Cost train:  4910.356728511222  Cost test:  5040.097747040375
Iteration :  106  Cost train:  4900.772363121738  Cost test:  5030.402369796365
Iteration :  107  Cost train:  4891.226251894862  Cost test:  5020.745468220809
Iteration :  108  Cost train:  4881.71824214399  Cost test:  5011.126889185576
Iteration :  109  Cost train:  4872.24818179195  Cost test:  5001.546480172844
Iteration :  110  Cost train:  4862.815919368562  Cost test:  4992.004089272664
Iteration :  111  Cost train:  4853.421304008225  Cost test:  4982.499565180531
Iteration :  112  Cost train:  4844.064185447495  Cost test:  4973.032757194979
Iteration :  113  Cost train:  4834.744414022687  Cost test:  4963.60351521517
Iteration :  114  Cost train:  4825.461840667478  Cost test:  4954.211689738496
Iteration :  115  Cost train:  4816.216316910526  Cost test:  4944.857131858197
Iteration :  116  Cost train:  4807.007694873094  Cost test:  4935.5396932609865
Iteration :  117  Cost train:  4797.83582726668  Cost test:  4926.259226224676
Iteration :  118  Cost train:  4788.70056739067  Cost test:  4917.015583615829
Iteration :  119  Cost train:  4779.601769129983  Cost test:  4907.808618887402
Iteration :  120  Cost train:  4770.53928695274  Cost test:  4898.638186076412
Iteration :  121  Cost train:  4761.512975907936  Cost test:  4889.5041398016065
Iteration :  122  Cost train:  4752.522691623114  Cost test:  4880.40633526114
Iteration :  123  Cost train:  4743.568290302064  Cost test:  4871.3446282302675
Iteration :  124  Cost train:  4734.649628722523  Cost test:  4862.31887505904
Iteration :  125  Cost train:  4725.766564233873  Cost test:  4853.328932670011
Iteration :  126  Cost train:  4716.91895475488  Cost test:  4844.3746585559575
Iteration :  127  Cost train:  4708.106658771398  Cost test:  4835.4559107776
Iteration :  128  Cost train:  4699.329535334121  Cost test:  4826.572547961344
Iteration :  129  Cost train:  4690.5874440563275  Cost test:  4817.724429297017
Iteration :  130  Cost train:  4681.880245111625  Cost test:  4808.911414535626
Iteration :  131  Cost train:  4673.207799231725  Cost test:  4800.133363987117
Iteration :  132  Cost train:  4664.56996770421  Cost test:  4791.390138518148
Iteration :  133  Cost train:  4655.966612370314  Cost test:  4782.681599549866
Iteration :  134  Cost train:  4647.397595622713  Cost test:  4774.007609055698
Iteration :  135  Cost train:  4638.862780403329  Cost test:  4765.368029559145
Iteration :  136  Cost train:  4630.36203020113  Cost test:  4756.762724131591
Iteration :  137  Cost train:  4621.895209049953  Cost test:  4748.19155639012
Iteration :  138  Cost train:  4613.4621815263245  Cost test:  4739.654390495332
Iteration :  139  Cost train:  4605.062812747297  Cost test:  4731.151091149184
Iteration :  140  Cost train:  4596.696968368294  Cost test:  4722.681523592823
Iteration :  141  Cost train:  4588.364514580952  Cost test:  4714.245553604445
Iteration :  142  Cost train:  4580.065318110995  Cost test:  4705.843047497141
Iteration :  143  Cost train:  4571.799246216084  Cost test:  4697.473872116774
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Iteration :  1799  Cost train:  2511.609049429105  Cost test:  2587.619039937356
Iteration :  1800  Cost train:  2511.5979519805037  Cost test:  2587.6041789342744
Iteration :  1801  Cost train:  2511.5868982212473  Cost test:  2587.589369122286
Iteration :  1802  Cost train:  2511.5758879769596  Cost test:  2587.5746103120273
Iteration :  1803  Cost train:  2511.5649210739566  Cost test:  2587.55990231486
Iteration :  1804  Cost train:  2511.553997339249  Cost test:  2587.545244942871
Iteration :  1805  Cost train:  2511.5431166005383  Cost test:  2587.5306380088646
Iteration :  1806  Cost train:  2511.5322786862134  Cost test:  2587.516081326366
Iteration :  1807  Cost train:  2511.5214834253475  Cost test:  2587.501574709612
Iteration :  1808  Cost train:  2511.5107306476975  Cost test:  2587.487117973553
Iteration :  1809  Cost train:  2511.5000201836992  Cost test:  2587.472710933848
Iteration :  1810  Cost train:  2511.489351864464  Cost test:  2587.458353406862
Iteration :  1811  Cost train:  2511.4787255217784  Cost test:  2587.4440452096646
Iteration :  1812  Cost train:  2511.468140988101  Cost test:  2587.4297861600244
Iteration :  1813  Cost train:  2511.457598096558  Cost test:  2587.41557607641
Iteration :  1814  Cost train:  2511.4470966809417  Cost test:  2587.401414777984
Iteration :  1815  Cost train:  2511.436636575709  Cost test:  2587.387302084602
Iteration :  1816  Cost train:  2511.426217615976  Cost test:  2587.3732378168106
Iteration :  1817  Cost train:  2511.415839637518  Cost test:  2587.3592217958408
Iteration :  1818  Cost train:  2511.4055024767645  Cost test:  2587.3452538436113
Iteration :  1819  Cost train:  2511.3952059708  Cost test:  2587.3313337827212
Iteration :  1820  Cost train:  2511.384949957358  Cost test:  2587.3174614364484
Iteration :  1821  Cost train:  2511.374734274818  Cost test:  2587.303636628748
Iteration :  1822  Cost train:  2511.3645587622077  Cost test:  2587.2898591842486
Iteration :  1823  Cost train:  2511.3544232591953  Cost test:  2587.2761289282507
Iteration :  1824  Cost train:  2511.34432760609  Cost test:  2587.262445686722
Iteration :  1825  Cost train:  2511.334271643838  Cost test:  2587.248809286299
Iteration :  1826  Cost train:  2511.3242552140186  Cost test:  2587.235219554278
Iteration :  1827  Cost train:  2511.3142781588476  Cost test:  2587.2216763186193
Convergence Achieved at  1827.0  iteration
Cost Minima Found :  2511.3142781588476
Betas : 
X0             41.611125
T1              1.186866
RH_1            2.209298
T2              1.139656
RH_2            2.130958
T3              1.228355
RH_3            2.123034
T4              1.142920
RH_4            2.097881
T5              1.062614
RH_5            2.669384
RH_6            2.439566
T7              1.106722
RH_7            1.838823
T8              1.208210
RH_8            2.199203
RH_9            2.182866
T_out           0.492207
Press_mm_hg    40.712834
RH_out          3.880083
Windspeed       0.252095
Tdewpoint       0.210227
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6105.395772226762  Cost test:  6247.571442739789
Iteration :  3  Cost train:  6062.41943323316  Cost test:  6204.187641859839
Iteration :  4  Cost train:  6019.9566634424455  Cost test:  6161.31984870631
Iteration :  5  Cost train:  5978.00132561409  Cost test:  6118.961911463421
Iteration :  6  Cost train:  5936.547355848659  Cost test:  6077.107751743354
Iteration :  7  Cost train:  5895.588762711358  Cost test:  6035.75136370931
Iteration :  8  Cost train:  5855.11962636607  Cost test:  5994.886813209025
Iteration :  9  Cost train:  5815.134097719745  Cost test:  5954.508236918646
Iteration :  10  Cost train:  5775.626397577002  Cost test:  5914.609841496838
Iteration :  11  Cost train:  5736.590815804839  Cost test:  5875.185902748987
Iteration :  12  Cost train:  5698.021710507333  Cost test:  5836.230764801391
Iteration :  13  Cost train:  5659.913507210189  Cost test:  5797.738839285322
Iteration :  14  Cost train:  5622.260698055041  Cost test:  5759.704604530831
Iteration :  15  Cost train:  5585.0578410033795  Cost test:  5722.1226047701775
Iteration :  16  Cost train:  5548.299559049998  Cost test:  5684.987449350796
Iteration :  17  Cost train:  5511.980539445824  Cost test:  5648.293811957639
Iteration :  18  Cost train:  5476.095532930059  Cost test:  5612.036429844826
Iteration :  19  Cost train:  5440.639352971473  Cost test:  5576.21010307647
Iteration :  20  Cost train:  5405.606875018779  Cost test:  5540.809693776566
Iteration :  21  Cost train:  5370.993035759964  Cost test:  5505.830125387852
Iteration :  22  Cost train:  5336.792832390464  Cost test:  5471.266381939514
Iteration :  23  Cost train:  5303.001321890099  Cost test:  5437.113507323644
Iteration :  24  Cost train:  5269.613620308622  Cost test:  5403.366604580333
Iteration :  25  Cost train:  5236.624902059843  Cost test:  5370.020835191325
Iteration :  26  Cost train:  5204.030399224158  Cost test:  5337.0714183820855
Iteration :  27  Cost train:  5171.825400859422  Cost test:  5304.513630432222
Iteration :  28  Cost train:  5140.005252320065  Cost test:  5272.342803994136
Iteration :  29  Cost train:  5108.56535458433  Cost test:  5240.554327419822
Iteration :  30  Cost train:  5077.501163589566  Cost test:  5209.143644095693
Iteration :  31  Cost train:  5046.808189575457  Cost test:  5178.106251785376
Iteration :  32  Cost train:  5016.481996435093  Cost test:  5147.437701980333
Iteration :  33  Cost train:  4986.518201073809  Cost test:  5117.133599258259
Iteration :  34  Cost train:  4956.912472775676  Cost test:  5087.189600649135
Iteration :  35  Cost train:  4927.660532577571  Cost test:  5057.601415008854
Iteration :  36  Cost train:  4898.758152650714  Cost test:  5028.364802400338
Iteration :  37  Cost train:  4870.201155689612  Cost test:  4999.475573482032
Iteration :  38  Cost train:  4841.98541430829  Cost test:  4970.929588903722
Iteration :  39  Cost train:  4814.10685044375  Cost test:  4942.722758709561
Iteration :  40  Cost train:  4786.561434766549  Cost test:  4914.851041748219
Iteration :  41  Cost train:  4759.345186098428  Cost test:  4887.310445090095
Iteration :  42  Cost train:  4732.4541708368915  Cost test:  4860.097023451479
Iteration :  43  Cost train:  4705.884502386676  Cost test:  4833.206878625598
Iteration :  44  Cost train:  4679.632340597998  Cost test:  4806.636158920457
Iteration :  45  Cost train:  4653.693891211531  Cost test:  4780.381058603395
Iteration :  46  Cost train:  4628.06540531  Cost test:  4754.43781735228
Iteration :  47  Cost train:  4602.743178776335  Cost test:  4728.802719713252
Iteration :  48  Cost train:  4577.723551758309  Cost test:  4703.4720945649515
Iteration :  49  Cost train:  4553.002908139559  Cost test:  4678.442314589142
Iteration :  50  Cost train:  4528.577675016933  Cost test:  4653.709795747664
Iteration :  51  Cost train:  4504.444322184094  Cost test:  4629.270996765627
Iteration :  52  Cost train:  4480.5993616212745  Cost test:  4605.122418620783
Iteration :  53  Cost train:  4457.039346991148  Cost test:  4581.260604038996
Iteration :  54  Cost train:  4433.760873140712  Cost test:  4557.682136995739
Iteration :  55  Cost train:  4410.760575609132  Cost test:  4534.383642223548
Iteration :  56  Cost train:  4388.035130141456  Cost test:  4511.361784725357
Iteration :  57  Cost train:  4365.581252208158  Cost test:  4488.6132692936435
Iteration :  58  Cost train:  4343.395696530404  Cost test:  4466.134840035325
Iteration :  59  Cost train:  4321.475256611002  Cost test:  4443.923279902332
Iteration :  60  Cost train:  4299.816764270952  Cost test:  4421.975410227771
Iteration :  61  Cost train:  4278.417089191546  Cost test:  4400.288090267656
Iteration :  62  Cost train:  4257.273138461918  Cost test:  4378.8582167480845
Iteration :  63  Cost train:  4236.381856132026  Cost test:  4357.68272341785
Iteration :  64  Cost train:  4215.74022277095  Cost test:  4336.758580606378
Iteration :  65  Cost train:  4195.3452550305  Cost test:  4316.082794786953
Iteration :  66  Cost train:  4175.194005214007  Cost test:  4295.65240814516
Iteration :  67  Cost train:  4155.283560850285  Cost test:  4275.464498152479
Iteration :  68  Cost train:  4135.611044272681  Cost test:  4255.516177144977
Iteration :  69  Cost train:  4116.17361220316  Cost test:  4235.804591907034
Iteration :  70  Cost train:  4096.968455341342  Cost test:  4216.326923260027
Iteration :  71  Cost train:  4077.992797958477  Cost test:  4197.080385655952
Iteration :  72  Cost train:  4059.2438974962515  Cost test:  4178.062226775875
Iteration :  73  Cost train:  4040.7190441703947  Cost test:  4159.269727133199
Iteration :  74  Cost train:  4022.4155605790265  Cost test:  4140.700199681654
Iteration :  75  Cost train:  4004.3308013156834  Cost test:  4122.350989427982
Iteration :  76  Cost train:  3986.4621525869625  Cost test:  4104.219473049246
Iteration :  77  Cost train:  3968.8070318347436  Cost test:  4086.3030585146985
Iteration :  78  Cost train:  3951.3628873629227  Cost test:  4068.5991847121836
Iteration :  79  Cost train:  3934.1271979686044  Cost test:  4051.1053210789933
Iteration :  80  Cost train:  3917.0974725777005  Cost test:  4033.8189672371304
Iteration :  81  Cost train:  3900.2712498848905  Cost test:  4016.7376526329326
Iteration :  82  Cost train:  3883.646097997877  Cost test:  3999.8589361810014
Iteration :  83  Cost train:  3867.219614085893  Cost test:  3983.1804059123797
Iteration :  84  Cost train:  3850.989424032416  Cost test:  3966.6996786269383
Iteration :  85  Cost train:  3834.9531820920242  Cost test:  3950.4143995499066
Iteration :  86  Cost train:  3819.108570551359  Cost test:  3934.322241992514
Iteration :  87  Cost train:  3803.453299394135  Cost test:  3918.420907016677
Iteration :  88  Cost train:  3787.9851059701577  Cost test:  3902.708123103698
Iteration :  89  Cost train:  3772.701754668293  Cost test:  3887.181645826919
Iteration :  90  Cost train:  3757.6010365933444  Cost test:  3871.839257528279
Iteration :  91  Cost train:  3742.6807692467946  Cost test:  3856.6787669987493
Iteration :  92  Cost train:  3727.9387962113615  Cost test:  3841.6980091625705
Iteration :  93  Cost train:  3713.372986839317  Cost test:  3826.8948447652683
Iteration :  94  Cost train:  3698.981235944547  Cost test:  3812.2671600653957
Iteration :  95  Cost train:  3684.7614634982706  Cost test:  3797.812866529956
Iteration :  96  Cost train:  3670.711614328411  Cost test:  3783.5299005334655
Iteration :  97  Cost train:  3656.8296578225522  Cost test:  3769.416223060605
Iteration :  98  Cost train:  3643.1135876344474  Cost test:  3755.4698194124317
Iteration :  99  Cost train:  3629.5614213940307  Cost test:  3741.688698916088
Iteration :  100  Cost train:  3616.171200420905  Cost test:  3728.070894637996
Iteration :  101  Cost train:  3602.9409894412374  Cost test:  3714.614463100455
Iteration :  102  Cost train:  3589.8688763080554  Cost test:  3701.317484001641
Iteration :  103  Cost train:  3576.95297172487  Cost test:  3688.178059938945
Iteration :  104  Cost train:  3564.1914089726115  Cost test:  3675.1943161356126
Iteration :  105  Cost train:  3551.5823436398246  Cost test:  3662.3644001706534
Iteration :  106  Cost train:  3539.1239533560915  Cost test:  3649.6864817119754
Iteration :  107  Cost train:  3526.8144375286324  Cost test:  3637.158752252701
Iteration :  108  Cost train:  3514.6520170820636  Cost test:  3624.779424850644
Iteration :  109  Cost train:  3502.634934201259  Cost test:  3612.5467338708836
Iteration :  110  Cost train:  3490.761452077286  Cost test:  3600.458934731426
Iteration :  111  Cost train:  3479.0298546563786  Cost test:  3588.514303651897
Iteration :  112  Cost train:  3467.438446391908  Cost test:  3576.711137405235
Iteration :  113  Cost train:  3455.985551999324  Cost test:  3565.0477530723574
Iteration :  114  Cost train:  3444.6695162140113  Cost test:  3553.5224877997425
Iteration :  115  Cost train:  3433.488703552054  Cost test:  3542.133698559927
Iteration :  116  Cost train:  3422.4414980738534  Cost test:  3530.8797619148445
Iteration :  117  Cost train:  3411.526303150564  Cost test:  3519.759073782002
Iteration :  118  Cost train:  3400.741541233332  Cost test:  3508.7700492034464
Iteration :  119  Cost train:  3390.0856536252854  Cost test:  3497.9111221174894
Iteration :  120  Cost train:  3379.5571002562488  Cost test:  3487.1807451331583
Iteration :  121  Cost train:  3369.154359460149  Cost test:  3476.5773893073415
Iteration :  122  Cost train:  3358.875927755087  Cost test:  3466.099543924596
Iteration :  123  Cost train:  3348.720319626031  Cost test:  3455.745716279584
Iteration :  124  Cost train:  3338.68606731011  Cost test:  3445.514431462108
Iteration :  125  Cost train:  3328.7717205844733  Cost test:  3435.4042321447128
Iteration :  126  Cost train:  3318.9758465566824  Cost test:  3425.413678372826
Iteration :  127  Cost train:  3309.2970294576107  Cost test:  3415.5413473573985
Iteration :  128  Cost train:  3299.7338704368185  Cost test:  3405.7858332700343
Iteration :  129  Cost train:  3290.2849873603677  Cost test:  3396.145747040553
Iteration :  130  Cost train:  3280.949014611062  Cost test:  3386.619716156976
Iteration :  131  Cost train:  3271.724602891063  Cost test:  3377.2063844679055
Iteration :  132  Cost train:  3262.6104190268775  Cost test:  3367.9044119872556
Iteration :  133  Cost train:  3253.605145776663  Cost test:  3358.7124747013213
Iteration :  134  Cost train:  3244.707481639845  Cost test:  3349.629264378149
Iteration :  135  Cost train:  3235.916140669007  Cost test:  3340.6534883791837
Iteration :  136  Cost train:  3227.229852284023  Cost test:  3331.783869473168
Iteration :  137  Cost train:  3218.6473610884204  Cost test:  3323.01914565226
Iteration :  138  Cost train:  3210.167426687933  Cost test:  3314.358069950348
Iteration :  139  Cost train:  3201.7888235112155  Cost test:  3305.799410263539
Iteration :  140  Cost train:  3193.5103406327157  Cost test:  3297.341949172785
Iteration :  141  Cost train:  3185.330781597648  Cost test:  3288.9844837686305
Iteration :  142  Cost train:  3177.2489642490696  Cost test:  3280.7258254780545
Iteration :  143  Cost train:  3169.2637205570163  Cost test:  3272.564799893379
Iteration :  144  Cost train:  3161.3738964496847  Cost test:  3264.500246603215
Iteration :  145  Cost train:  3153.5783516466254  Cost test:  3256.531019025441
Iteration :  146  Cost train:  3145.87595949394  Cost test:  3248.6559842421602
Iteration :  147  Cost train:  3138.2656068014385  Cost test:  3240.874022836641
Iteration :  148  Cost train:  3130.746193681745  Cost test:  3233.184028732198
Iteration :  149  Cost train:  3123.316633391325  Cost test:  3225.5849090329966
Iteration :  150  Cost train:  3115.975852173422  Cost test:  3218.0755838667674
Iteration :  151  Cost train:  3108.7227891028538  Cost test:  3210.6549862293873
Iteration :  152  Cost train:  3101.5563959326787  Cost test:  3203.3220618313208
Iteration :  153  Cost train:  3094.475636942687  Cost test:  3196.0757689459006
Iteration :  154  Cost train:  3087.479488789703  Cost test:  3188.915078259414
Iteration :  155  Cost train:  3080.5669403596785  Cost test:  3181.838972722976
Iteration :  156  Cost train:  3073.736992621555  Cost test:  3174.846447406183
Iteration :  157  Cost train:  3066.9886584828655  Cost test:  3167.9365093525034
Iteration :  158  Cost train:  3060.3209626470684  Cost test:  3161.1081774364025
Iteration :  159  Cost train:  3053.7329414725837  Cost test:  3154.360482222159
Iteration :  160  Cost train:  3047.223642833516  Cost test:  3147.6924658243956
Iteration :  161  Cost train:  3040.792125982037  Cost test:  3141.1031817702424
Iteration :  162  Cost train:  3034.4374614124185  Cost test:  3134.5916948631693
Iteration :  163  Cost train:  3028.1587307266846  Cost test:  3128.157081048435
Iteration :  164  Cost train:  3021.955026501875  Cost test:  3121.798427280143
Iteration :  165  Cost train:  3015.8254521588906  Cost test:  3115.514831389888
Iteration :  166  Cost train:  3009.7691218329064  Cost test:  3109.3054019569695
Iteration :  167  Cost train:  3003.7851602453334  Cost test:  3103.1692581801517
Iteration :  168  Cost train:  2997.872702577316  Cost test:  3097.105529750962
Iteration :  169  Cost train:  2992.0308943447308  Cost test:  3091.1133567284955
Iteration :  170  Cost train:  2986.2588912746874  Cost test:  3085.1918894157175
Iteration :  171  Cost train:  2980.5558591835033  Cost test:  3079.3402882372447
Iteration :  172  Cost train:  2974.920973856133  Cost test:  3073.557723618581
Iteration :  173  Cost train:  2969.3534209270447  Cost test:  3067.8433758667966
Iteration :  174  Cost train:  2963.852395762515  Cost test:  3062.1964350526396
Iteration :  175  Cost train:  2958.417103344331  Cost test:  3056.616100894046
Iteration :  176  Cost train:  2953.046758154885  Cost test:  3051.101582641039
Iteration :  177  Cost train:  2947.740584063641  Cost test:  3045.6520989620135
Iteration :  178  Cost train:  2942.4978142149575  Cost test:  3040.2668778313678
Iteration :  179  Cost train:  2937.3176909172475  Cost test:  3034.9451564184847
Iteration :  180  Cost train:  2932.199465533472  Cost test:  3029.686180978032
Iteration :  181  Cost train:  2927.1423983729323  Cost test:  3024.4892067415776
Iteration :  182  Cost train:  2922.1457585843623  Cost test:  3019.3534978104954
Iteration :  183  Cost train:  2917.2088240502912  Cost test:  3014.2783270501513
Iteration :  184  Cost train:  2912.3308812826813  Cost test:  3009.2629759853535
Iteration :  185  Cost train:  2907.511225319798  Cost test:  3004.3067346970474
Iteration :  186  Cost train:  2902.74915962432  Cost test:  2999.408901720253
Iteration :  187  Cost train:  2898.043995982668  Cost test:  2994.5687839432057
Iteration :  188  Cost train:  2893.395054405534  Cost test:  2989.785696507717
Iteration :  189  Cost train:  2888.8016630295997  Cost test:  2985.0589627107156
Iteration :  190  Cost train:  2884.263158020428  Cost test:  2980.387913906967
Iteration :  191  Cost train:  2879.7788834765197  Cost test:  2975.7718894129516
Iteration :  192  Cost train:  2875.3481913345104  Cost test:  2971.2102364118973
Iteration :  193  Cost train:  2870.9704412755054  Cost test:  2966.702309859938
Iteration :  194  Cost train:  2866.645000632531  Cost test:  2962.247472393398
Iteration :  195  Cost train:  2862.371244299092  Cost test:  2957.84509423718
Iteration :  196  Cost train:  2858.1485546388244  Cost test:  2953.4945531142484
Iteration :  197  Cost train:  2853.976321396227  Cost test:  2949.195234156195
Iteration :  198  Cost train:  2849.8539416084554  Cost test:  2944.946529814868
Iteration :  199  Cost train:  2845.7808195181738  Cost test:  2940.7478397750597
Iteration :  200  Cost train:  2841.756366487452  Cost test:  2936.5985708682365
Iteration :  201  Cost train:  2837.780000912684  Cost test:  2932.4981369872967
Iteration :  202  Cost train:  2833.8511481405258  Cost test:  2928.4459590023475
Iteration :  203  Cost train:  2829.9692403848417  Cost test:  2924.4414646774867
Iteration :  204  Cost train:  2826.133716644638  Cost test:  2920.484088588579
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Iteration :  686  Cost train:  2509.792846979738  Cost test:  2585.0360677173544
Iteration :  687  Cost train:  2509.7808591202115  Cost test:  2585.017371744919
Iteration :  688  Cost train:  2509.7690090906376  Cost test:  2584.9988536566716
Iteration :  689  Cost train:  2509.757295243976  Cost test:  2584.9805115655386
Iteration :  690  Cost train:  2509.7457159528694  Cost test:  2584.962343605567
Iteration :  691  Cost train:  2509.734269609406  Cost test:  2584.944347931681
Iteration :  692  Cost train:  2509.72295462489  Cost test:  2584.9265227194405
Iteration :  693  Cost train:  2509.7117694296116  Cost test:  2584.9088661648043
Iteration :  694  Cost train:  2509.7007124726165  Cost test:  2584.891376483891
Iteration :  695  Cost train:  2509.689782221487  Cost test:  2584.8740519127523
Iteration :  696  Cost train:  2509.6789771621184  Cost test:  2584.856890707138
Iteration :  697  Cost train:  2509.6682957984967  Cost test:  2584.839891142273
Iteration :  698  Cost train:  2509.65773665249  Cost test:  2584.8230515126274
Iteration :  699  Cost train:  2509.647298263626  Cost test:  2584.8063701317014
Iteration :  700  Cost train:  2509.6369791888874  Cost test:  2584.7898453318003
Iteration :  701  Cost train:  2509.6267780025023  Cost test:  2584.7734754638204
Iteration :  702  Cost train:  2509.616693295735  Cost test:  2584.7572588970356
Iteration :  703  Cost train:  2509.6067236766853  Cost test:  2584.741194018883
Convergence Achieved at  703.0  iteration
Cost Minima Found :  2509.6067236766853
Betas : 
X0             42.094477
T1              1.203854
RH_1            2.241598
T2              1.160149
RH_2            2.148825
T3              1.247312
RH_3            2.149755
T4              1.159418
RH_4            2.122465
T5              1.076593
RH_5            2.696330
RH_6            2.393892
T7              1.122040
RH_7            1.851109
T8              1.225701
RH_8            2.209071
RH_9            2.200891
T_out           0.512659
Press_mm_hg    41.196422
RH_out          3.863044
Windspeed       0.260234
Tdewpoint       0.214124
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6076.543611838325  Cost test:  6218.446003772223
Iteration :  3  Cost train:  6005.633386796533  Cost test:  6146.859399558619
Iteration :  4  Cost train:  5936.132632479871  Cost test:  6076.689012665105
Iteration :  5  Cost train:  5868.013332772901  Cost test:  6007.906759765801
Iteration :  6  Cost train:  5801.248028437821  Cost test:  5940.485115080273
Iteration :  7  Cost train:  5735.8098060453885  Cost test:  5874.397099297848
Iteration :  8  Cost train:  5671.672287125855  Cost test:  5809.616268722021
Iteration :  9  Cost train:  5608.809617535555  Cost test:  5746.116704630562
Iteration :  10  Cost train:  5547.196457034842  Cost test:  5683.87300284706
Iteration :  11  Cost train:  5486.8079690732075  Cost test:  5622.860263519675
Iteration :  12  Cost train:  5427.619810777418  Cost test:  5563.054081103009
Iteration :  13  Cost train:  5369.608123138673  Cost test:  5504.43053453903
Iteration :  14  Cost train:  5312.74952139481  Cost test:  5446.966177633123
Iteration :  15  Cost train:  5257.021085603679  Cost test:  5390.6380296213565
Iteration :  16  Cost train:  5202.400351403891  Cost test:  5335.423565925204
Iteration :  17  Cost train:  5148.865300959232  Cost test:  5281.300709089947
Iteration :  18  Cost train:  5096.394354083038  Cost test:  5228.247819903164
Iteration :  19  Cost train:  5044.966359539036  Cost test:  5176.243688689674
Iteration :  20  Cost train:  4994.560586515062  Cost test:  5125.267526779468
Iteration :  21  Cost train:  4945.156716266281  Cost test:  5075.298958145163
Iteration :  22  Cost train:  4896.734833924501  Cost test:  5026.31801120563
Iteration :  23  Cost train:  4849.275420470297  Cost test:  4978.305110792478
Iteration :  24  Cost train:  4802.759344864711  Cost test:  4931.241070276168
Iteration :  25  Cost train:  4757.16785633734  Cost test:  4885.107083848575
Iteration :  26  Cost train:  4712.482576827724  Cost test:  4839.884718958901
Iteration :  27  Cost train:  4668.685493576975  Cost test:  4795.555908899881
Iteration :  28  Cost train:  4625.758951866656  Cost test:  4752.102945541294
Iteration :  29  Cost train:  4583.685647901994  Cost test:  4709.508472207868
Iteration :  30  Cost train:  4542.448621836558  Cost test:  4667.755476698692
Iteration :  31  Cost train:  4502.031250935582  Cost test:  4626.827284445319
Iteration :  32  Cost train:  4462.417242875173  Cost test:  4586.707551805829
Iteration :  33  Cost train:  4423.590629174728  Cost test:  4547.380259492129
Iteration :  34  Cost train:  4385.535758759877  Cost test:  4508.829706127837
Iteration :  35  Cost train:  4348.237291653396  Cost test:  4471.040501934186
Iteration :  36  Cost train:  4311.6801927915  Cost test:  4433.997562541363
Iteration :  37  Cost train:  4275.849725963077  Cost test:  4397.686102922821
Iteration :  38  Cost train:  4240.73144786937  Cost test:  4362.091631450112
Iteration :  39  Cost train:  4206.311202301752  Cost test:  4327.199944065832
Iteration :  40  Cost train:  4172.575114435217  Cost test:  4292.997118572359
Iteration :  41  Cost train:  4139.509585235305  Cost test:  4259.469509034043
Iteration :  42  Cost train:  4107.101285976204  Cost test:  4226.603740290647
Iteration :  43  Cost train:  4075.337152867807  Cost test:  4194.386702579767
Iteration :  44  Cost train:  4044.2043817895783  Cost test:  4162.8055462661205
Iteration :  45  Cost train:  4013.6904231290837  Cost test:  4131.847676675532
Iteration :  46  Cost train:  3983.7829767231246  Cost test:  4101.5007490315875
Iteration :  47  Cost train:  3954.4699868994226  Cost test:  4071.752663492855
Iteration :  48  Cost train:  3925.739637616864  Cost test:  4042.5915602887335
Iteration :  49  Cost train:  3897.580347702337  Cost test:  4014.005814951927
Iteration :  50  Cost train:  3869.9807661822497  Cost test:  3985.9840336456423
Iteration :  51  Cost train:  3842.9297677068453  Cost test:  3958.515048583634
Iteration :  52  Cost train:  3816.416448065467  Cost test:  3931.5879135412233
Iteration :  53  Cost train:  3790.4301197909617  Cost test:  3905.191899455526
Iteration :  54  Cost train:  3764.960307851464  Cost test:  3879.316490113071
Iteration :  55  Cost train:  3739.9967454278076  Cost test:  3853.95137792311
Iteration :  56  Cost train:  3715.5293697748716  Cost test:  3829.086459774892
Iteration :  57  Cost train:  3691.548318165192  Cost test:  3804.7118329772475
Iteration :  58  Cost train:  3668.0439239132  Cost test:  3780.8177912788346
Iteration :  59  Cost train:  3645.00671247849  Cost test:  3757.3948209674595
Iteration :  60  Cost train:  3622.42739764654  Cost test:  3734.4335970468837
Iteration :  61  Cost train:  3600.2968777853484  Cost test:  3711.9249794895895
Iteration :  62  Cost train:  3578.606232176483  Cost test:  3689.860009563992
Iteration :  63  Cost train:  3557.346717419045  Cost test:  3668.2299062346137
Iteration :  64  Cost train:  3536.5097639051287  Cost test:  3647.0260626337745
Iteration :  65  Cost train:  3516.0869723653254  Cost test:  3626.2400426033837
Iteration :  66  Cost train:  3496.0701104828986  Cost test:  3605.863577305423
Iteration :  67  Cost train:  3476.4511095752564  Cost test:  3585.8885618997747
Iteration :  68  Cost train:  3457.22206134139  Cost test:  3566.307052288046
Iteration :  69  Cost train:  3438.37521467396  Cost test:  3547.1112619220753
Iteration :  70  Cost train:  3419.902972534752  Cost test:  3528.2935586758504
Iteration :  71  Cost train:  3401.7978888922344  Cost test:  3509.846461779557
Iteration :  72  Cost train:  3384.0526657199953  Cost test:  3491.7626388145445
Iteration :  73  Cost train:  3366.660150054835  Cost test:  3474.034902767981
Iteration :  74  Cost train:  3349.613331113338  Cost test:  3456.6562091460173
Iteration :  75  Cost train:  3332.9053374657624  Cost test:  3439.6196531443125
Iteration :  76  Cost train:  3316.5294342660923  Cost test:  3422.918466874747
Iteration :  77  Cost train:  3300.479020537167  Cost test:  3406.546016647244
Iteration :  78  Cost train:  3284.7476265097544  Cost test:  3390.4958003055795
Iteration :  79  Cost train:  3269.3289110145306  Cost test:  3374.761444616113
Iteration :  80  Cost train:  3254.2166589258927  Cost test:  3359.3367027084014
Iteration :  81  Cost train:  3239.4047786565775  Cost test:  3344.2154515666402
Iteration :  82  Cost train:  3224.8872997020894  Cost test:  3329.3916895709476
Iteration :  83  Cost train:  3210.658370233931  Cost test:  3314.8595340874776
Iteration :  84  Cost train:  3196.7122547406734  Cost test:  3300.6132191064194
Iteration :  85  Cost train:  3183.0433317159172  Cost test:  3286.6470929268958
Iteration :  86  Cost train:  3169.6460913922106  Cost test:  3272.955615887865
Iteration :  87  Cost train:  3156.5151335200057  Cost test:  3259.533358144085
Iteration :  88  Cost train:  3143.6451651907687  Cost test:  3246.374997486264
Iteration :  89  Cost train:  3131.0309987033575  Cost test:  3233.475317204504
Iteration :  90  Cost train:  3118.6675494728083  Cost test:  3220.8292039941803
Iteration :  91  Cost train:  3106.549833980692  Cost test:  3208.431645903428
Iteration :  92  Cost train:  3094.672967766207  Cost test:  3196.2777303213907
Iteration :  93  Cost train:  3083.0321634572088  Cost test:  3184.3626420064243
Iteration :  94  Cost train:  3071.622728840375  Cost test:  3172.681661153476
Iteration :  95  Cost train:  3060.440064969724  Cost test:  3161.2301614998464
Iteration :  96  Cost train:  3049.4796643127434  Cost test:  3150.0036084685676
Iteration :  97  Cost train:  3038.7371089333515  Cost test:  3138.997557348675
Iteration :  98  Cost train:  3028.2080687109924  Cost test:  3128.2076515116064
Iteration :  99  Cost train:  3017.8882995951185  Cost test:  3117.6296206630377
Iteration :  100  Cost train:  3007.773641894374  Cost test:  3107.259279129434
Iteration :  101  Cost train:  2997.860018599782  Cost test:  3097.0925241786404
Iteration :  102  Cost train:  2988.1434337412657  Cost test:  3087.125334373817
Iteration :  103  Cost train:  2978.619970776831  Cost test:  3077.353767960081
Iteration :  104  Cost train:  2969.2857910137755  Cost test:  3067.7739612831806
Iteration :  105  Cost train:  2960.137132061269  Cost test:  3058.3821272395794
Iteration :  106  Cost train:  2951.170306313702  Cost test:  3049.1745537573315
Iteration :  107  Cost train:  2942.381699464173  Cost test:  3040.1476023071114
Iteration :  108  Cost train:  2933.767769047528  Cost test:  3031.297706442832
Iteration :  109  Cost train:  2925.3250430123617  Cost test:  3022.6213703712356
Iteration :  110  Cost train:  2917.0501183213937  Cost test:  3014.115167549901
Iteration :  111  Cost train:  2908.9396595796793  Cost test:  3005.7757393130873
Iteration :  112  Cost train:  2900.9903976900705  Cost test:  2997.5997935248747
Iteration :  113  Cost train:  2893.199128535421  Cost test:  2989.5841032590474
Iteration :  114  Cost train:  2885.562711686968  Cost test:  2981.7255055052024
Iteration :  115  Cost train:  2878.078069138401  Cost test:  2974.020899900541
Iteration :  116  Cost train:  2870.742184065083  Cost test:  2966.4672474868617
Iteration :  117  Cost train:  2863.552099607945  Cost test:  2959.0615694922258
Iteration :  118  Cost train:  2856.5049176815382  Cost test:  2951.800946136822
Iteration :  119  Cost train:  2849.5977978058017  Cost test:  2944.6825154625462
Iteration :  120  Cost train:  2842.827955961025  Cost test:  2937.7034721858263
Iteration :  121  Cost train:  2836.192663465589  Cost test:  2930.8610665732167
Iteration :  122  Cost train:  2829.6892458760058  Cost test:  2924.1526033393393
Iteration :  123  Cost train:  2823.3150819088305  Cost test:  2917.5754405666926
Iteration :  124  Cost train:  2817.067602383987  Cost test:  2911.1269886469195
Iteration :  125  Cost train:  2810.944289189114  Cost test:  2904.8047092430984
Iteration :  126  Cost train:  2804.942674264489  Cost test:  2898.6061142726417
Iteration :  127  Cost train:  2799.0603386081257  Cost test:  2892.5287649103802
Iteration :  128  Cost train:  2793.2949113006566  Cost test:  2886.5702706114625
Iteration :  129  Cost train:  2787.644068549587  Cost test:  2880.7282881536394
Iteration :  130  Cost train:  2782.105532752555  Cost test:  2875.000520698574
Iteration :  131  Cost train:  2776.67707157921  Cost test:  2869.384716871786
Iteration :  132  Cost train:  2771.3564970713323  Cost test:  2863.878669860872
Iteration :  133  Cost train:  2766.141664760855  Cost test:  2858.480216531622
Iteration :  134  Cost train:  2761.0304728053998  Cost test:  2853.187236561694
Iteration :  135  Cost train:  2756.02086114101  Cost test:  2847.997651591485
Iteration :  136  Cost train:  2751.110810651714  Cost test:  2842.909424391865
Iteration :  137  Cost train:  2746.298342355607  Cost test:  2837.920558048433
Iteration :  138  Cost train:  2741.5815166070975  Cost test:  2833.0290951619736
Iteration :  139  Cost train:  2736.958432315022  Cost test:  2828.2331170647813
Iteration :  140  Cost train:  2732.427226176293  Cost test:  2823.530743052551
Iteration :  141  Cost train:  2727.986071924787  Cost test:  2818.920129631517
Iteration :  142  Cost train:  2723.633179595159  Cost test:  2814.399469780536
Iteration :  143  Cost train:  2719.3667948012876  Cost test:  2809.9669922278244
Iteration :  144  Cost train:  2715.1851980290667  Cost test:  2805.620960742054
Iteration :  145  Cost train:  2711.0867039432533  Cost test:  2801.3596734375205
Iteration :  146  Cost train:  2707.0696607080913  Cost test:  2797.1814620931063
Iteration :  147  Cost train:  2703.1324493214424  Cost test:  2793.084691484767
Iteration :  148  Cost train:  2699.273482962148  Cost test:  2789.0677587312653
Iteration :  149  Cost train:  2695.4912063503702  Cost test:  2785.1290926528973
Iteration :  150  Cost train:  2691.78409512064  Cost test:  2781.267153142947
Iteration :  151  Cost train:  2688.1506552073715  Cost test:  2777.4804305516204
Iteration :  152  Cost train:  2684.589422242593  Cost test:  2773.7674450822074
Iteration :  153  Cost train:  2681.0989609656417  Cost test:  2770.126746199233
Iteration :  154  Cost train:  2677.6778646445987  Cost test:  2766.5569120483556
Iteration :  155  Cost train:  2674.3247545092204  Cost test:  2763.0565488877796
Iteration :  156  Cost train:  2671.0382791951465  Cost test:  2759.624290530961
Iteration :  157  Cost train:  2667.817114199147  Cost test:  2756.258797800364
Iteration :  158  Cost train:  2664.6599613452054  Cost test:  2752.9587579920744
Iteration :  159  Cost train:  2661.565548261212  Cost test:  2749.7228843510293
Iteration :  160  Cost train:  2658.5326278660546  Cost test:  2746.549915556668
Iteration :  161  Cost train:  2655.5599778669134  Cost test:  2743.4386152187903
Iteration :  162  Cost train:  2652.646400266539  Cost test:  2740.387771383425
Iteration :  163  Cost train:  2649.7907208803294  Cost test:  2737.396196048502
Iteration :  164  Cost train:  2646.991788863005  Cost test:  2734.46272468914
Iteration :  165  Cost train:  2644.2484762446916  Cost test:  2731.5862157923543
Iteration :  166  Cost train:  2641.5596774762257  Cost test:  2728.7655504010036
Iteration :  167  Cost train:  2638.924308983497  Cost test:  2725.9996316667816
Iteration :  168  Cost train:  2636.3413087306462  Cost test:  2723.287384412088
Iteration :  169  Cost train:  2633.809635791952  Cost test:  2720.6277547005907
Iteration :  170  Cost train:  2631.328269932224  Cost test:  2718.0197094163073
Iteration :  171  Cost train:  2628.896211195531  Cost test:  2715.4622358510514
Iteration :  172  Cost train:  2626.5124795021156  Cost test:  2712.9543413000542
Iteration :  173  Cost train:  2624.1761142533114  Cost test:  2710.495052665618
Iteration :  174  Cost train:  2621.8861739443155  Cost test:  2708.083416068634
Iteration :  175  Cost train:  2619.6417357846594  Cost test:  2705.7184964678086
Iteration :  176  Cost train:  2617.4418953262266  Cost test:  2703.3993772864483
Iteration :  177  Cost train:  2615.285766098657  Cost test:  2701.1251600466467
Iteration :  178  Cost train:  2613.172479252002  Cost test:  2698.894964010735
Iteration :  179  Cost train:  2611.101183206487  Cost test:  2696.707925829845
Iteration :  180  Cost train:  2609.071043309226  Cost test:  2694.563199199446
Iteration :  181  Cost train:  2607.081241497768  Cost test:  2692.4599545217193
Iteration :  182  Cost train:  2605.130975970329  Cost test:  2690.3973785746257
Iteration :  183  Cost train:  2603.219460862576  Cost test:  2688.3746741875484
Iteration :  184  Cost train:  2601.345925930837  Cost test:  2686.391059923363
Iteration :  185  Cost train:  2599.509616241611  Cost test:  2684.4457697668254
Iteration :  186  Cost train:  2597.7097918672453  Cost test:  2682.5380528191295
Iteration :  187  Cost train:  2595.9457275876634  Cost test:  2680.6671729985396
Iteration :  188  Cost train:  2594.2167125980227  Cost test:  2678.832408746951
Iteration :  189  Cost train:  2592.5220502221805  Cost test:  2677.033052742277
Iteration :  190  Cost train:  2590.8610576318615  Cost test:  2675.2684116165465
Iteration :  191  Cost train:  2589.2330655713968  Cost test:  2673.5378056795826
Iteration :  192  Cost train:  2587.6374180879448  Cost test:  2671.840568648176
Iteration :  193  Cost train:  2586.0734722670704  Cost test:  2670.176047380623
Iteration :  194  Cost train:  2584.5405979735774  Cost test:  2668.5436016165345
Iteration :  195  Cost train:  2583.038177597497  Cost test:  2666.9426037218
Iteration :  196  Cost train:  2581.565605805123  Cost test:  2665.37243843862
Iteration :  197  Cost train:  2580.122289294996  Cost test:  2663.832502640492
Iteration :  198  Cost train:  2578.7076465587356  Cost test:  2662.322205092053
Iteration :  199  Cost train:  2577.3211076466328  Cost test:  2660.840966213694
Iteration :  200  Cost train:  2575.962113937895  Cost test:  2659.388217850839
Iteration :  201  Cost train:  2574.6301179154607  Cost test:  2657.963403047799
Iteration :  202  Cost train:  2573.3245829452912  Cost test:  2656.565975826115
Iteration :  203  Cost train:  2572.0449830600483  Cost test:  2655.195400967296
Iteration :  204  Cost train:  2570.7908027470703  Cost test:  2653.851153799866
Iteration :  205  Cost train:  2569.5615367405653  Cost test:  2652.5327199906346
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Iteration :  207  Cost train:  2567.1757766001356  Cost test:  2649.9712855819585
Iteration :  208  Cost train:  2566.0183213560385  Cost test:  2648.7273061864676
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Iteration :  216  Cost train:  2557.549114107446  Cost test:  2639.5962844802752
Iteration :  217  Cost train:  2556.5828726524805  Cost test:  2638.550988644081
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Iteration :  273  Cost train:  2524.399349087267  Cost test:  2602.9973096418503
Iteration :  274  Cost train:  2524.091167239588  Cost test:  2602.644497836337
Iteration :  275  Cost train:  2523.789096059157  Cost test:  2602.2982420302033
Iteration :  276  Cost train:  2523.493014084193  Cost test:  2601.958416314316
Iteration :  277  Cost train:  2523.202802267215  Cost test:  2601.6248972382496
Iteration :  278  Cost train:  2522.918343927054  Cost test:  2601.297563761854
Iteration :  279  Cost train:  2522.639524701821  Cost test:  2600.976297207779
Iteration :  280  Cost train:  2522.3662325027994  Cost test:  2600.6609812149445
Iteration :  281  Cost train:  2522.0983574692677  Cost test:  2600.3515016929186
Iteration :  282  Cost train:  2521.8357919242117  Cost test:  2600.0477467772134
Iteration :  283  Cost train:  2521.578430330916  Cost test:  2599.7496067854527
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Iteration :  288  Cost train:  2520.3661323869646  Cost test:  2598.339439208389
Iteration :  289  Cost train:  2520.137892834847  Cost test:  2598.072802321435
Iteration :  290  Cost train:  2519.9141749367805  Cost test:  2597.81107017729
Iteration :  291  Cost train:  2519.6948888158713  Cost test:  2597.5541490732166
Iteration :  292  Cost train:  2519.4799463817153  Cost test:  2597.3019471311704
Iteration :  293  Cost train:  2519.2692612948854  Cost test:  2597.0543742619025
Iteration :  294  Cost train:  2519.0627489321237  Cost test:  2596.8113421297817
Iteration :  295  Cost train:  2518.8603263522386  Cost test:  2596.5727641183075
Iteration :  296  Cost train:  2518.6619122626585  Cost test:  2596.3385552963036
Iteration :  297  Cost train:  2518.467426986673  Cost test:  2596.1086323847844
Iteration :  298  Cost train:  2518.276792431306  Cost test:  2595.8829137244725
Iteration :  299  Cost train:  2518.089932055841  Cost test:  2595.6613192439595
Iteration :  300  Cost train:  2517.906770840964  Cost test:  2595.443770428498
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Iteration :  302  Cost train:  2517.5512532418916  Cost test:  2595.0205033340762
Iteration :  303  Cost train:  2517.3787541569104  Cost test:  2594.8146355365916
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Iteration :  307  Cost train:  2516.7222230081197  Cost test:  2594.02792514277
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Iteration :  319  Cost train:  2515.03994193215  Cost test:  2591.9850104294874
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Iteration :  321  Cost train:  2514.796692907073  Cost test:  2591.685761535254
Iteration :  322  Cost train:  2514.678660040324  Cost test:  2591.540146907686
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Iteration :  326  Cost train:  2514.229380597065  Cost test:  2590.983263818435
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Iteration :  328  Cost train:  2514.017825624606  Cost test:  2590.719503267196
Iteration :  329  Cost train:  2513.9151688795087  Cost test:  2590.5911335330866
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Iteration :  343  Cost train:  2512.673374457036  Cost test:  2589.015149214489
Iteration :  344  Cost train:  2512.597215484573  Cost test:  2588.916865799509
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Iteration :  346  Cost train:  2512.449364011911  Cost test:  2588.725424946343
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Iteration :  348  Cost train:  2512.307272180758  Cost test:  2588.540608497683
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Iteration :  351  Cost train:  2512.1044403228766  Cost test:  2588.2752736404586
Iteration :  352  Cost train:  2512.039469598004  Cost test:  2588.189882561155
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Iteration :  355  Cost train:  2511.8521146481144  Cost test:  2587.9424797341057
Iteration :  356  Cost train:  2511.7920991767614  Cost test:  2587.8628459900347
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Iteration :  359  Cost train:  2511.6190268105097  Cost test:  2587.632084246104
Iteration :  360  Cost train:  2511.563584205075  Cost test:  2587.557793883245
Iteration :  361  Cost train:  2511.5092285775113  Cost test:  2587.4847783414884
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Iteration :  363  Cost train:  2511.4036922627597  Cost test:  2587.3424782423963
Iteration :  364  Cost train:  2511.35246964406  Cost test:  2587.273148057374
Iteration :  365  Cost train:  2511.3022501233036  Cost test:  2587.2050014208085
Iteration :  366  Cost train:  2511.253013762104  Cost test:  2587.138016592044
Iteration :  367  Cost train:  2511.204741018388  Cost test:  2587.072172244741
Iteration :  368  Cost train:  2511.1574127385234  Cost test:  2587.007447458817
Iteration :  369  Cost train:  2511.1110101495938  Cost test:  2586.943821712549
Iteration :  370  Cost train:  2511.065514851836  Cost test:  2586.8812748748296
Iteration :  371  Cost train:  2511.0209088112156  Cost test:  2586.8197871975754
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Iteration :  373  Cost train:  2510.9342941504515  Cost test:  2586.6999122027387
Iteration :  374  Cost train:  2510.892251226201  Cost test:  2586.641487237856
Iteration :  375  Cost train:  2510.851028937046  Cost test:  2586.5840461246717
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Iteration :  377  Cost train:  2510.770981341986  Cost test:  2586.472044027034
Iteration :  378  Cost train:  2510.732124379183  Cost test:  2586.417448174055
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Iteration :  389  Cost train:  2510.3515120352235  Cost test:  2585.873719477485
Iteration :  390  Cost train:  2510.3208122615215  Cost test:  2585.8290623386315
Iteration :  391  Cost train:  2510.2907076583692  Cost test:  2585.785139369988
Iteration :  392  Cost train:  2510.2611863957695  Cost test:  2585.7419373532634
Iteration :  393  Cost train:  2510.2322368788723  Cost test:  2585.6994433191785
Iteration :  394  Cost train:  2510.203847743298  Cost test:  2585.657644542652
Iteration :  395  Cost train:  2510.1760078505563  Cost test:  2585.616528538083
Iteration :  396  Cost train:  2510.14870628356  Cost test:  2585.576083054724
Iteration :  397  Cost train:  2510.121932342219  Cost test:  2585.5362960721473
Iteration :  398  Cost train:  2510.095675539131  Cost test:  2585.497155795797
Iteration :  399  Cost train:  2510.0699255953505  Cost test:  2585.458650652632
Iteration :  400  Cost train:  2510.044672436248  Cost test:  2585.4207692868513
Iteration :  401  Cost train:  2510.019906187448  Cost test:  2585.3835005557007
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Iteration :  403  Cost train:  2509.9717959007207  Cost test:  2585.3107574669607
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Iteration :  405  Cost train:  2509.925519595947  Cost test:  2585.240336351263
Iteration :  406  Cost train:  2509.9030465176675  Cost test:  2585.2059708255883
Iteration :  407  Cost train:  2509.881005091314  Cost test:  2585.172155327545
Iteration :  408  Cost train:  2509.8593867371574  Cost test:  2585.1388800950886
Iteration :  409  Cost train:  2509.8381830460085  Cost test:  2585.1061355485217
Iteration :  410  Cost train:  2509.8173857758284  Cost test:  2585.0739122869886
Iteration :  411  Cost train:  2509.796986848405  Cost test:  2585.0422010850334
Iteration :  412  Cost train:  2509.7769783460976  Cost test:  2585.01099288923
Iteration :  413  Cost train:  2509.7573525086436  Cost test:  2584.9802788148745
Iteration :  414  Cost train:  2509.7381017300336  Cost test:  2584.9500501427456
Iteration :  415  Cost train:  2509.7192185554413  Cost test:  2584.9202983159244
Iteration :  416  Cost train:  2509.7006956782207  Cost test:  2584.891014936678
Iteration :  417  Cost train:  2509.6825259369625  Cost test:  2584.8621917634073
Iteration :  418  Cost train:  2509.6647023126006  Cost test:  2584.8338207076476
Iteration :  419  Cost train:  2509.647217925592  Cost test:  2584.8058938311347
Iteration :  420  Cost train:  2509.630066033136  Cost test:  2584.778403342922
Iteration :  421  Cost train:  2509.613240026459  Cost test:  2584.7513415965586
Iteration :  422  Cost train:  2509.5967334281513  Cost test:  2584.72470108732
Iteration :  423  Cost train:  2509.5805398895536  Cost test:  2584.6984744494957
Iteration :  424  Cost train:  2509.564653188201  Cost test:  2584.672654453723
Iteration :  425  Cost train:  2509.5490672253113  Cost test:  2584.6472340043815
Iteration :  426  Cost train:  2509.5337760233283  Cost test:  2584.6222061370327
Iteration :  427  Cost train:  2509.518773723513  Cost test:  2584.597564015909
Iteration :  428  Cost train:  2509.5040545835786  Cost test:  2584.5733009314577
Iteration :  429  Cost train:  2509.489612975381  Cost test:  2584.549410297925
Iteration :  430  Cost train:  2509.4754433826456  Cost test:  2584.5258856509927
Iteration :  431  Cost train:  2509.4615403987436  Cost test:  2584.502720645458
Iteration :  432  Cost train:  2509.447898724516  Cost test:  2584.479909052961
Iteration :  433  Cost train:  2509.434513166135  Cost test:  2584.457444759753
Iteration :  434  Cost train:  2509.42137863301  Cost test:  2584.435321764511
Iteration :  435  Cost train:  2509.408490135737  Cost test:  2584.4135341761953
Iteration :  436  Cost train:  2509.395842784086  Cost test:  2584.392076211945
Iteration :  437  Cost train:  2509.383431785032  Cost test:  2584.3709421950166
Iteration :  438  Cost train:  2509.3712524408184  Cost test:  2584.350126552767
Iteration :  439  Cost train:  2509.359300147068  Cost test:  2584.3296238146663
Iteration :  440  Cost train:  2509.3475703909257  Cost test:  2584.3094286103574
Iteration :  441  Cost train:  2509.3360587492366  Cost test:  2584.2895356677504
Iteration :  442  Cost train:  2509.324760886766  Cost test:  2584.269939811153
Iteration :  443  Cost train:  2509.3136725544514  Cost test:  2584.250635959439
Iteration :  444  Cost train:  2509.3027895876885  Cost test:  2584.2316191242517
Iteration :  445  Cost train:  2509.2921079046523  Cost test:  2584.212884408241
Iteration :  446  Cost train:  2509.281623504655  Cost test:  2584.1944270033378
Iteration :  447  Cost train:  2509.2713324665265  Cost test:  2584.176242189057
Iteration :  448  Cost train:  2509.2612309470423  Cost test:  2584.1583253308404
Iteration :  449  Cost train:  2509.251315179368  Cost test:  2584.1406718784237
Convergence Achieved at  449.0  iteration
Cost Minima Found :  2509.251315179368
Betas : 
X0             42.248227
T1              1.209825
RH_1            2.253051
T2              1.167956
RH_2            2.153287
T3              1.254174
RH_3            2.158621
T4              1.165238
RH_4            2.130324
T5              1.081330
RH_5            2.704182
RH_6            2.366238
T7              1.127348
RH_7            1.853407
T8              1.231878
RH_8            2.209428
RH_9            2.205324
T_out           0.521779
Press_mm_hg    41.352139
RH_out          3.846602
Windspeed       0.263749
Tdewpoint       0.215621
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
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Iteration :  241  Cost train:  2509.0016990851027  Cost test:  2583.6667947606966
Iteration :  242  Cost train:  2508.9912379428406  Cost test:  2583.6454658888033
Iteration :  243  Cost train:  2508.9811307745204  Cost test:  2583.6247064622826
Iteration :  244  Cost train:  2508.9713635807425  Cost test:  2583.6044981774653
Convergence Achieved at  244.0  iteration
Cost Minima Found :  2508.9713635807425
Betas : 
X0             42.409463
T1              1.216730
RH_1            2.266395
T2              1.177598
RH_2            2.156583
T3              1.262312
RH_3            2.168333
T4              1.171987
RH_4            2.138609
T5              1.086625
RH_5            2.711602
RH_6            2.322392
T7              1.133409
RH_7            1.853996
T8              1.239049
RH_8            2.206655
RH_9            2.208502
T_out           0.534300
Press_mm_hg    41.517579
RH_out          3.816893
Windspeed       0.268481
Tdewpoint       0.217483
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  5458.090953727054  Cost test:  5593.844183375483
Iteration :  3  Cost train:  4898.396593841184  Cost test:  5027.9990775749275
Iteration :  4  Cost train:  4444.925921509985  Cost test:  4568.9913373497575
Iteration :  5  Cost train:  4077.518602760957  Cost test:  4196.599453630689
Iteration :  6  Cost train:  3779.8405600792935  Cost test:  3894.4342611933566
Iteration :  7  Cost train:  3538.6577821324577  Cost test:  3649.212144716861
Iteration :  8  Cost train:  3343.247958107909  Cost test:  3450.1661289236836
Iteration :  9  Cost train:  3184.9237787483157  Cost test:  3288.5686891025316
Iteration :  10  Cost train:  3056.6467107139833  Cost test:  3157.3450834089203
Iteration :  11  Cost train:  2952.7140732200373  Cost test:  3050.7600311547317
Iteration :  12  Cost train:  2868.5055048126464  Cost test:  2964.1638206683483
Iteration :  13  Cost train:  2800.277548551223  Cost test:  2893.7865711214154
Iteration :  14  Cost train:  2744.997223140666  Cost test:  2836.5715123692717
Iteration :  15  Cost train:  2700.2071808186133  Cost test:  2790.039880451825
Iteration :  16  Cost train:  2663.9164571056704  Cost test:  2752.1814310116947
Iteration :  17  Cost train:  2634.511955305088  Cost test:  2721.36571094288
Iteration :  18  Cost train:  2610.6867304763578  Cost test:  2696.2701506726885
Iteration :  19  Cost train:  2591.3818844883403  Cost test:  2675.8217865882443
Iteration :  20  Cost train:  2575.739488887138  Cost test:  2659.1500284540034
Iteration :  21  Cost train:  2563.0644425951596  Cost test:  2645.5483771336985
Iteration :  22  Cost train:  2552.7935686879405  Cost test:  2634.4433953279245
Iteration :  23  Cost train:  2544.4705763345805  Cost test:  2625.369556029334
Iteration :  24  Cost train:  2537.7257747446292  Cost test:  2617.9488542910167
Iteration :  25  Cost train:  2532.259637231835  Cost test:  2611.8742792945413
Iteration :  26  Cost train:  2527.8294846759777  Cost test:  2606.8964149861845
Iteration :  27  Cost train:  2524.238696348098  Cost test:  2602.812576334268
Iteration :  28  Cost train:  2521.327968427485  Cost test:  2599.4580007140507
Iteration :  29  Cost train:  2518.9682315762857  Cost test:  2596.6987050456423
Iteration :  30  Cost train:  2517.0549126970027  Cost test:  2594.4256931433615
Iteration :  31  Cost train:  2515.5032857586298  Cost test:  2592.550257561647
Iteration :  32  Cost train:  2514.2447049956377  Cost test:  2591.0001687008366
Iteration :  33  Cost train:  2513.2235530131193  Cost test:  2589.716583218979
Iteration :  34  Cost train:  2512.394768115092  Cost test:  2588.651535628028
Iteration :  35  Cost train:  2511.7218409244315  Cost test:  2587.7659027478967
Iteration :  36  Cost train:  2511.1751912269597  Cost test:  2587.0277515952143
Iteration :  37  Cost train:  2510.7308528764443  Cost test:  2586.410998223294
Iteration :  38  Cost train:  2510.369408293214  Cost test:  2585.8943187576906
Iteration :  39  Cost train:  2510.075125185692  Cost test:  2585.4602649970207
Iteration :  40  Cost train:  2509.8352571146957  Cost test:  2585.0945459651753
Iteration :  41  Cost train:  2509.639476804558  Cost test:  2584.7854441085515
Iteration :  42  Cost train:  2509.4794170068826  Cost test:  2584.5233407546593
Iteration :  43  Cost train:  2509.3482985043765  Cost test:  2584.3003302490033
Iteration :  44  Cost train:  2509.2406287163267  Cost test:  2584.1099060782567
Iteration :  45  Cost train:  2509.151957506139  Cost test:  2583.946705441938
Iteration :  46  Cost train:  2509.07867933449  Cost test:  2583.8063012916878
Iteration :  47  Cost train:  2509.0178729620975  Cost test:  2583.685032930149
Iteration :  48  Cost train:  2508.9671715755026  Cost test:  2583.5798679420113
Iteration :  49  Cost train:  2508.9246575618663  Cost test:  2583.488289592425
Iteration :  50  Cost train:  2508.8887772545872  Cost test:  2583.408204932905
Iteration :  51  Cost train:  2508.8582718594625  Cost test:  2583.3378697508742
Iteration :  52  Cost train:  2508.8321214904663  Cost test:  2583.275827225711
Iteration :  53  Cost train:  2508.8094998270503  Cost test:  2583.2208577435995
Iteration :  54  Cost train:  2508.7897373770966  Cost test:  2583.17193780166
Iteration :  55  Cost train:  2508.77229171224  Cost test:  2583.128206319784
Iteration :  56  Cost train:  2508.7567233522745  Cost test:  2583.0889369934057
Iteration :  57  Cost train:  2508.7426762264813  Cost test:  2583.0535155759235
Iteration :  58  Cost train:  2508.729861843235  Cost test:  2583.0214211868947
Iteration :  59  Cost train:  2508.7180464640765  Cost test:  2582.992210910488
Iteration :  60  Cost train:  2508.707040712038  Cost test:  2582.9655070854333
Iteration :  61  Cost train:  2508.696691152218  Cost test:  2582.9409867987747
Iteration :  62  Cost train:  2508.6868734702844  Cost test:  2582.9183731859903
Convergence Achieved at  62.0  iteration
Cost Minima Found :  2508.6868734702844
Betas : 
X0             42.660242
T1              1.231842
RH_1            2.296235
T2              1.202512
RH_2            2.152303
T3              1.281375
RH_3            2.186267
T4              1.186883
RH_4            2.151801
T5              1.097090
RH_5            2.717603
RH_6            2.153156
T7              1.146194
RH_7            1.842512
T8              1.254923
RH_8            2.180914
RH_9            2.203428
T_out           0.573908
Press_mm_hg    41.789467
RH_out          3.685805
Windspeed       0.282968
Tdewpoint       0.222364
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  2509.068747327288  Cost test:  2583.2888315125174
Iteration :  3  Cost train:  2508.9877646352675  Cost test:  2583.1244482109373
Iteration :  4  Cost train:  2508.911792909118  Cost test:  2583.044290973536
Iteration :  5  Cost train:  2508.8359407048074  Cost test:  2582.9643506341044
Iteration :  6  Cost train:  2508.76020780163  Cost test:  2582.884535248296
Iteration :  7  Cost train:  2508.6845939858417  Cost test:  2582.8048444897763
Iteration :  8  Cost train:  2508.6090990440857  Cost test:  2582.7252781388083
Iteration :  9  Cost train:  2508.53372276339  Cost test:  2582.6458359761696
Iteration :  10  Cost train:  2508.458464931171  Cost test:  2582.566517783033
Iteration :  11  Cost train:  2508.383325335225  Cost test:  2582.487323340963
Iteration :  12  Cost train:  2508.308303763738  Cost test:  2582.4082524319147
Iteration :  13  Cost train:  2508.233400005275  Cost test:  2582.329304838237
Iteration :  14  Cost train:  2508.1586138487864  Cost test:  2582.2504803426664
Iteration :  15  Cost train:  2508.0839450836033  Cost test:  2582.1717787283305
Iteration :  16  Cost train:  2508.0093934994384  Cost test:  2582.093199778746
Iteration :  17  Cost train:  2507.934958886385  Cost test:  2582.014743277816
Iteration :  18  Cost train:  2507.8606410349175  Cost test:  2581.9364090098334
Iteration :  19  Cost train:  2507.7864397358876  Cost test:  2581.858196759477
Iteration :  20  Cost train:  2507.712354780527  Cost test:  2581.780106311811
Iteration :  21  Cost train:  2507.6383859604443  Cost test:  2581.702137452287
Iteration :  22  Cost train:  2507.5645330676266  Cost test:  2581.6242899667386
Iteration :  23  Cost train:  2507.4907958944355  Cost test:  2581.546563641386
Iteration :  24  Cost train:  2507.417174233611  Cost test:  2581.468958262831
Iteration :  25  Cost train:  2507.343667878267  Cost test:  2581.39147361806
Iteration :  26  Cost train:  2507.2702766218904  Cost test:  2581.314109494439
Iteration :  27  Cost train:  2507.1970002583444  Cost test:  2581.236865679717
Iteration :  28  Cost train:  2507.1238385818647  Cost test:  2581.1597419620225
Iteration :  29  Cost train:  2507.050791387058  Cost test:  2581.082738129865
Iteration :  30  Cost train:  2506.977858468904  Cost test:  2581.005853972133
Iteration :  31  Cost train:  2506.9050396227535  Cost test:  2580.9290892780923
Iteration :  32  Cost train:  2506.832334644328  Cost test:  2580.852443837388
Iteration :  33  Cost train:  2506.759743329717  Cost test:  2580.775917440042
Iteration :  34  Cost train:  2506.6872654753815  Cost test:  2580.699509876453
Iteration :  35  Cost train:  2506.614900878149  Cost test:  2580.623220937394
Iteration :  36  Cost train:  2506.542649335216  Cost test:  2580.547050414015
Iteration :  37  Cost train:  2506.470510644145  Cost test:  2580.4709980978396
Iteration :  38  Cost train:  2506.398484602866  Cost test:  2580.395063780765
Iteration :  39  Cost train:  2506.326571009675  Cost test:  2580.3192472550627
Iteration :  40  Cost train:  2506.254769663231  Cost test:  2580.243548313376
Iteration :  41  Cost train:  2506.183080362559  Cost test:  2580.1679667487183
Iteration :  42  Cost train:  2506.1115029070484  Cost test:  2580.092502354477
Iteration :  43  Cost train:  2506.04003709645  Cost test:  2580.017154924407
Iteration :  44  Cost train:  2505.968682730878  Cost test:  2579.941924252636
Iteration :  45  Cost train:  2505.897439610809  Cost test:  2579.8668101336584
Iteration :  46  Cost train:  2505.826307537079  Cost test:  2579.791812362339
Iteration :  47  Cost train:  2505.7552863108867  Cost test:  2579.7169307339086
Iteration :  48  Cost train:  2505.684375733789  Cost test:  2579.6421650439656
Iteration :  49  Cost train:  2505.613575607702  Cost test:  2579.5675150884754
Iteration :  50  Cost train:  2505.542885734901  Cost test:  2579.4929806637683
Iteration :  51  Cost train:  2505.472305918019  Cost test:  2579.418561566541
Iteration :  52  Cost train:  2505.4018359600473  Cost test:  2579.3442575938543
Iteration :  53  Cost train:  2505.331475664331  Cost test:  2579.270068543132
Iteration :  54  Cost train:  2505.2612248345736  Cost test:  2579.1959942121607
Iteration :  55  Cost train:  2505.191083274832  Cost test:  2579.1220343990913
Iteration :  56  Cost train:  2505.121050789521  Cost test:  2579.048188902436
Iteration :  57  Cost train:  2505.051127183407  Cost test:  2578.9744575210666
Iteration :  58  Cost train:  2504.981312261608  Cost test:  2578.9008400542175
Iteration :  59  Cost train:  2504.911605829598  Cost test:  2578.827336301482
Iteration :  60  Cost train:  2504.842007693202  Cost test:  2578.7539460628122
Iteration :  61  Cost train:  2504.772517658596  Cost test:  2578.6806691385204
Iteration :  62  Cost train:  2504.7031355323074  Cost test:  2578.607505329275
Iteration :  63  Cost train:  2504.633861121213  Cost test:  2578.5344544361033
Iteration :  64  Cost train:  2504.5646942325407  Cost test:  2578.4615162603877
Iteration :  65  Cost train:  2504.495634673865  Cost test:  2578.3886906038674
Iteration :  66  Cost train:  2504.426682253111  Cost test:  2578.3159772686377
Iteration :  67  Cost train:  2504.357836778549  Cost test:  2578.2433760571475
Iteration :  68  Cost train:  2504.2890980587986  Cost test:  2578.170886772201
Iteration :  69  Cost train:  2504.2204659028253  Cost test:  2578.098509216954
Iteration :  70  Cost train:  2504.151940119939  Cost test:  2578.026243194917
Iteration :  71  Cost train:  2504.0835205197964  Cost test:  2577.954088509951
Iteration :  72  Cost train:  2504.0152069123974  Cost test:  2577.88204496627
Iteration :  73  Cost train:  2503.9469991080864  Cost test:  2577.8101123684387
Iteration :  74  Cost train:  2503.878896917552  Cost test:  2577.7382905213717
Iteration :  75  Cost train:  2503.8109001518233  Cost test:  2577.666579230333
Iteration :  76  Cost train:  2503.743008622273  Cost test:  2577.5949783009364
Iteration :  77  Cost train:  2503.6752221406146  Cost test:  2577.523487539144
Iteration :  78  Cost train:  2503.607540518902  Cost test:  2577.4521067512637
Iteration :  79  Cost train:  2503.5399635695317  Cost test:  2577.3808357439543
Iteration :  80  Cost train:  2503.4724911052363  Cost test:  2577.3096743242168
Iteration :  81  Cost train:  2503.40512293909  Cost test:  2577.238622299402
Iteration :  82  Cost train:  2503.337858884502  Cost test:  2577.1676794772034
Iteration :  83  Cost train:  2503.270698755224  Cost test:  2577.09684566566
Iteration :  84  Cost train:  2503.2036423653412  Cost test:  2577.0261206731557
Iteration :  85  Cost train:  2503.1366895292763  Cost test:  2576.9555043084156
Iteration :  86  Cost train:  2503.0698400617875  Cost test:  2576.8849963805096
Iteration :  87  Cost train:  2503.0030937779693  Cost test:  2576.8145966988486
Iteration :  88  Cost train:  2502.9364504932496  Cost test:  2576.7443050731863
Iteration :  89  Cost train:  2502.869910023391  Cost test:  2576.6741213136165
Iteration :  90  Cost train:  2502.80347218449  Cost test:  2576.6040452305724
Iteration :  91  Cost train:  2502.7371367929754  Cost test:  2576.5340766348286
Iteration :  92  Cost train:  2502.6709036656075  Cost test:  2576.464215337498
Iteration :  93  Cost train:  2502.6047726194797  Cost test:  2576.394461150032
Iteration :  94  Cost train:  2502.5387434720155  Cost test:  2576.3248138842196
Iteration :  95  Cost train:  2502.472816040969  Cost test:  2576.255273352188
Iteration :  96  Cost train:  2502.406990144424  Cost test:  2576.1858393664
Iteration :  97  Cost train:  2502.3412656007945  Cost test:  2576.1165117396554
Iteration :  98  Cost train:  2502.2756422288217  Cost test:  2576.047290285088
Iteration :  99  Cost train:  2502.210119847576  Cost test:  2575.978174816168
Iteration :  100  Cost train:  2502.1446982764546  Cost test:  2575.9091651466997
Iteration :  101  Cost train:  2502.0793773351816  Cost test:  2575.8402610908192
Iteration :  102  Cost train:  2502.0141568438075  Cost test:  2575.771462462999
Iteration :  103  Cost train:  2501.9490366227083  Cost test:  2575.7027690780396
Iteration :  104  Cost train:  2501.884016492586  Cost test:  2575.6341807510776
Iteration :  105  Cost train:  2501.819096274466  Cost test:  2575.565697297578
Iteration :  106  Cost train:  2501.7542757896977  Cost test:  2575.4973185333374
Iteration :  107  Cost train:  2501.689554859954  Cost test:  2575.4290442744837
Iteration :  108  Cost train:  2501.6249333072315  Cost test:  2575.3608743374707
Iteration :  109  Cost train:  2501.560410953848  Cost test:  2575.292808539086
Iteration :  110  Cost train:  2501.495987622442  Cost test:  2575.2248466964406
Iteration :  111  Cost train:  2501.4316631359743  Cost test:  2575.1569886269767
Iteration :  112  Cost train:  2501.3674373177264  Cost test:  2575.0892341484623
Iteration :  113  Cost train:  2501.3033099912986  Cost test:  2575.0215830789907
Iteration :  114  Cost train:  2501.23928098061  Cost test:  2574.9540352369836
Iteration :  115  Cost train:  2501.175350109901  Cost test:  2574.8865904411855
Iteration :  116  Cost train:  2501.111517203726  Cost test:  2574.8192485106674
Iteration :  117  Cost train:  2501.0477820869614  Cost test:  2574.752009264824
Iteration :  118  Cost train:  2500.984144584797  Cost test:  2574.684872523373
Iteration :  119  Cost train:  2500.9206045227406  Cost test:  2574.6178381063555
Iteration :  120  Cost train:  2500.8571617266152  Cost test:  2574.550905834135
Iteration :  121  Cost train:  2500.79381602256  Cost test:  2574.4840755273967
Iteration :  122  Cost train:  2500.7305672370276  Cost test:  2574.4173470071473
Iteration :  123  Cost train:  2500.6674151967854  Cost test:  2574.3507200947142
Iteration :  124  Cost train:  2500.6043597289136  Cost test:  2574.2841946117437
Iteration :  125  Cost train:  2500.5414006608066  Cost test:  2574.217770380203
Iteration :  126  Cost train:  2500.4785378201705  Cost test:  2574.151447222378
Iteration :  127  Cost train:  2500.4157710350223  Cost test:  2574.085224960873
Iteration :  128  Cost train:  2500.3531001336924  Cost test:  2574.0191034186087
Iteration :  129  Cost train:  2500.290524944819  Cost test:  2573.9530824188246
Iteration :  130  Cost train:  2500.228045297353  Cost test:  2573.8871617850764
Iteration :  131  Cost train:  2500.165661020553  Cost test:  2573.8213413412354
Iteration :  132  Cost train:  2500.1033719439883  Cost test:  2573.755620911489
Iteration :  133  Cost train:  2500.0411778975363  Cost test:  2573.6900003203395
Iteration :  134  Cost train:  2499.97907871138  Cost test:  2573.624479392603
Iteration :  135  Cost train:  2499.917074216012  Cost test:  2573.5590579534096
Iteration :  136  Cost train:  2499.855164242232  Cost test:  2573.4937358282027
Iteration :  137  Cost train:  2499.7933486211446  Cost test:  2573.428512842738
Iteration :  138  Cost train:  2499.7316271841596  Cost test:  2573.363388823085
Iteration :  139  Cost train:  2499.669999762994  Cost test:  2573.2983635956225
Iteration :  140  Cost train:  2499.608466189667  Cost test:  2573.233436987041
Iteration :  141  Cost train:  2499.5470262965036  Cost test:  2573.1686088243414
Iteration :  142  Cost train:  2499.485679916131  Cost test:  2573.1038789348363
Iteration :  143  Cost train:  2499.4244268814805  Cost test:  2573.039247146143
Iteration :  144  Cost train:  2499.363267025785  Cost test:  2572.9747132861926
Iteration :  145  Cost train:  2499.3022001825784  Cost test:  2572.9102771832218
Iteration :  146  Cost train:  2499.241226185697  Cost test:  2572.845938665775
Iteration :  147  Cost train:  2499.1803448692776  Cost test:  2572.7816975627047
Iteration :  148  Cost train:  2499.119556067758  Cost test:  2572.717553703168
Iteration :  149  Cost train:  2499.058859615873  Cost test:  2572.6535069166307
Iteration :  150  Cost train:  2498.998255348659  Cost test:  2572.589557032861
Iteration :  151  Cost train:  2498.93774310145  Cost test:  2572.5257038819345
Iteration :  152  Cost train:  2498.877322709878  Cost test:  2572.46194729423
Iteration :  153  Cost train:  2498.816994009873  Cost test:  2572.3982871004296
Iteration :  154  Cost train:  2498.75675683766  Cost test:  2572.3347231315192
Iteration :  155  Cost train:  2498.6966110297635  Cost test:  2572.271255218788
Iteration :  156  Cost train:  2498.6365564230005  Cost test:  2572.2078831938256
Iteration :  157  Cost train:  2498.5765928544865  Cost test:  2572.1446068885252
Iteration :  158  Cost train:  2498.516720161628  Cost test:  2572.0814261350793
Iteration :  159  Cost train:  2498.4569381821307  Cost test:  2572.018340765982
Iteration :  160  Cost train:  2498.3972467539884  Cost test:  2571.955350614028
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Iteration :  1818  Cost train:  2456.9253341655904  Cost test:  2528.8289429172432
Iteration :  1819  Cost train:  2456.914400760597  Cost test:  2528.818300061881
Iteration :  1820  Cost train:  2456.903472844161  Cost test:  2528.8076634801637
Iteration :  1821  Cost train:  2456.8925504081544  Cost test:  2528.797033163117
Iteration :  1822  Cost train:  2456.8816334444605  Cost test:  2528.7864091017814
Iteration :  1823  Cost train:  2456.870721944981  Cost test:  2528.775791287215
Iteration :  1824  Cost train:  2456.859815901628  Cost test:  2528.765179710489
Iteration :  1825  Cost train:  2456.8489153063297  Cost test:  2528.7545743626906
Iteration :  1826  Cost train:  2456.838020151029  Cost test:  2528.743975234923
Iteration :  1827  Cost train:  2456.8271304276823  Cost test:  2528.7333823183026
Iteration :  1828  Cost train:  2456.8162461282604  Cost test:  2528.722795603963
Iteration :  1829  Cost train:  2456.80536724475  Cost test:  2528.712215083052
Iteration :  1830  Cost train:  2456.794493769149  Cost test:  2528.7016407467318
Iteration :  1831  Cost train:  2456.7836256934725  Cost test:  2528.691072586181
Iteration :  1832  Cost train:  2456.7727630097475  Cost test:  2528.6805105925923
Iteration :  1833  Cost train:  2456.7619057100164  Cost test:  2528.6699547571734
Iteration :  1834  Cost train:  2456.7510537863345  Cost test:  2528.6594050711483
Iteration :  1835  Cost train:  2456.7402072307746  Cost test:  2528.6488615257545
Iteration :  1836  Cost train:  2456.729366035419  Cost test:  2528.6383241122444
Iteration :  1837  Cost train:  2456.718530192367  Cost test:  2528.6277928218856
Iteration :  1838  Cost train:  2456.7076996937303  Cost test:  2528.617267645962
Iteration :  1839  Cost train:  2456.696874531637  Cost test:  2528.60674857577
Iteration :  1840  Cost train:  2456.6860546982257  Cost test:  2528.596235602622
Iteration :  1841  Cost train:  2456.675240185652  Cost test:  2528.5857287178455
Iteration :  1842  Cost train:  2456.664430986084  Cost test:  2528.5752279127823
Iteration :  1843  Cost train:  2456.6536270917045  Cost test:  2528.5647331787895
Iteration :  1844  Cost train:  2456.6428284947087  Cost test:  2528.554244507237
Iteration :  1845  Cost train:  2456.6320351873073  Cost test:  2528.543761889512
Iteration :  1846  Cost train:  2456.621247161724  Cost test:  2528.533285317015
Iteration :  1847  Cost train:  2456.6104644101965  Cost test:  2528.522814781161
Iteration :  1848  Cost train:  2456.599686924976  Cost test:  2528.512350273381
Iteration :  1849  Cost train:  2456.5889146983286  Cost test:  2528.501891785118
Iteration :  1850  Cost train:  2456.5781477225314  Cost test:  2528.491439307832
Iteration :  1851  Cost train:  2456.567385989879  Cost test:  2528.480992832996
Iteration :  1852  Cost train:  2456.5566294926757  Cost test:  2528.4705523520997
Iteration :  1853  Cost train:  2456.5458782232436  Cost test:  2528.4601178566436
Iteration :  1854  Cost train:  2456.5351321739145  Cost test:  2528.449689338147
Iteration :  1855  Cost train:  2456.524391337037  Cost test:  2528.43926678814
Iteration :  1856  Cost train:  2456.513655704971  Cost test:  2528.4288501981687
Iteration :  1857  Cost train:  2456.5029252700906  Cost test:  2528.418439559793
Iteration :  1858  Cost train:  2456.4922000247843  Cost test:  2528.408034864589
Iteration :  1859  Cost train:  2456.4814799614533  Cost test:  2528.397636104145
Iteration :  1860  Cost train:  2456.4707650725127  Cost test:  2528.387243270063
Iteration :  1861  Cost train:  2456.4600553503897  Cost test:  2528.3768563539634
Iteration :  1862  Cost train:  2456.4493507875277  Cost test:  2528.3664753474754
Iteration :  1863  Cost train:  2456.4386513763807  Cost test:  2528.3561002422466
Iteration :  1864  Cost train:  2456.4279571094175  Cost test:  2528.345731029937
Iteration :  1865  Cost train:  2456.4172679791204  Cost test:  2528.3353677022205
Iteration :  1866  Cost train:  2456.406583977984  Cost test:  2528.3250102507864
Iteration :  1867  Cost train:  2456.395905098517  Cost test:  2528.314658667337
Iteration :  1868  Cost train:  2456.385231333242  Cost test:  2528.3043129435896
Iteration :  1869  Cost train:  2456.374562674693  Cost test:  2528.293973071275
Iteration :  1870  Cost train:  2456.363899115419  Cost test:  2528.2836390421385
Iteration :  1871  Cost train:  2456.3532406479812  Cost test:  2528.2733108479383
Iteration :  1872  Cost train:  2456.342587264955  Cost test:  2528.2629884804483
Iteration :  1873  Cost train:  2456.3319389589274  Cost test:  2528.2526719314546
Iteration :  1874  Cost train:  2456.3212957225005  Cost test:  2528.2423611927597
Iteration :  1875  Cost train:  2456.3106575482875  Cost test:  2528.2320562561777
Iteration :  1876  Cost train:  2456.300024428917  Cost test:  2528.2217571135366
Iteration :  1877  Cost train:  2456.2893963570277  Cost test:  2528.21146375668
Iteration :  1878  Cost train:  2456.278773325274  Cost test:  2528.2011761774647
Iteration :  1879  Cost train:  2456.2681553263224  Cost test:  2528.190894367761
Iteration :  1880  Cost train:  2456.2575423528524  Cost test:  2528.1806183194517
Iteration :  1881  Cost train:  2456.246934397556  Cost test:  2528.170348024437
Iteration :  1882  Cost train:  2456.2363314531385  Cost test:  2528.1600834746273
Iteration :  1883  Cost train:  2456.225733512319  Cost test:  2528.149824661949
Iteration :  1884  Cost train:  2456.2151405678283  Cost test:  2528.13957157834
Iteration :  1885  Cost train:  2456.2045526124098  Cost test:  2528.1293242157544
Iteration :  1886  Cost train:  2456.1939696388217  Cost test:  2528.119082566158
Iteration :  1887  Cost train:  2456.183391639833  Cost test:  2528.108846621532
Iteration :  1888  Cost train:  2456.1728186082273  Cost test:  2528.0986163738694
Iteration :  1889  Cost train:  2456.1622505367986  Cost test:  2528.0883918151776
Iteration :  1890  Cost train:  2456.151687418356  Cost test:  2528.078172937478
Iteration :  1891  Cost train:  2456.1411292457205  Cost test:  2528.0679597328044
Iteration :  1892  Cost train:  2456.130576011725  Cost test:  2528.057752193206
Iteration :  1893  Cost train:  2456.120027709217  Cost test:  2528.0475503107436
Iteration :  1894  Cost train:  2456.109484331055  Cost test:  2528.0373540774926
Iteration :  1895  Cost train:  2456.0989458701106  Cost test:  2528.027163485541
Iteration :  1896  Cost train:  2456.088412319268  Cost test:  2528.016978526991
Iteration :  1897  Cost train:  2456.077883671425  Cost test:  2528.0067991939577
Iteration :  1898  Cost train:  2456.0673599194897  Cost test:  2527.99662547857
Iteration :  1899  Cost train:  2456.0568410563856  Cost test:  2527.98645737297
Iteration :  1900  Cost train:  2456.046327075047  Cost test:  2527.976294869313
Iteration :  1901  Cost train:  2456.0358179684204  Cost test:  2527.9661379597674
Iteration :  1902  Cost train:  2456.0253137294662  Cost test:  2527.9559866365157
Iteration :  1903  Cost train:  2456.0148143511556  Cost test:  2527.9458408917526
Iteration :  1904  Cost train:  2456.0043198264743  Cost test:  2527.935700717687
Iteration :  1905  Cost train:  2455.993830148419  Cost test:  2527.92556610654
Iteration :  1906  Cost train:  2455.9833453099986  Cost test:  2527.9154370505466
Iteration :  1907  Cost train:  2455.9728653042357  Cost test:  2527.9053135419554
Iteration :  1908  Cost train:  2455.962390124164  Cost test:  2527.895195573027
Iteration :  1909  Cost train:  2455.9519197628297  Cost test:  2527.8850831360364
Iteration :  1910  Cost train:  2455.941454213292  Cost test:  2527.8749762232696
Iteration :  1911  Cost train:  2455.930993468622  Cost test:  2527.8648748270284
Iteration :  1912  Cost train:  2455.920537521903  Cost test:  2527.8547789396257
Iteration :  1913  Cost train:  2455.9100863662306  Cost test:  2527.8446885533886
Iteration :  1914  Cost train:  2455.899639994713  Cost test:  2527.8346036606554
Iteration :  1915  Cost train:  2455.8891984004704  Cost test:  2527.82452425378
Iteration :  1916  Cost train:  2455.878761576633  Cost test:  2527.8144503251274
Iteration :  1917  Cost train:  2455.8683295163487  Cost test:  2527.804381867076
Iteration :  1918  Cost train:  2455.8579022127715  Cost test:  2527.794318872017
Iteration :  1919  Cost train:  2455.847479659071  Cost test:  2527.784261332355
Iteration :  1920  Cost train:  2455.8370618484273  Cost test:  2527.7742092405065
Iteration :  1921  Cost train:  2455.8266487740343  Cost test:  2527.7641625889023
Iteration :  1922  Cost train:  2455.8162404290956  Cost test:  2527.7541213699837
Iteration :  1923  Cost train:  2455.805836806829  Cost test:  2527.7440855762084
Iteration :  1924  Cost train:  2455.7954379004636  Cost test:  2527.7340552000433
Iteration :  1925  Cost train:  2455.7850437032394  Cost test:  2527.7240302339696
Iteration :  1926  Cost train:  2455.7746542084105  Cost test:  2527.7140106704815
Iteration :  1927  Cost train:  2455.7642694092406  Cost test:  2527.7039965020854
Iteration :  1928  Cost train:  2455.7538892990074  Cost test:  2527.6939877213003
Iteration :  1929  Cost train:  2455.7435138709984  Cost test:  2527.683984320659
Iteration :  1930  Cost train:  2455.733143118515  Cost test:  2527.6739862927047
Iteration :  1931  Cost train:  2455.722777034869  Cost test:  2527.6639936299957
Iteration :  1932  Cost train:  2455.7124156133855  Cost test:  2527.654006325101
Iteration :  1933  Cost train:  2455.7020588473997  Cost test:  2527.644024370604
Iteration :  1934  Cost train:  2455.69170673026  Cost test:  2527.634047759098
Iteration :  1935  Cost train:  2455.6813592553253  Cost test:  2527.624076483192
Iteration :  1936  Cost train:  2455.671016415968  Cost test:  2527.6141105355046
Iteration :  1937  Cost train:  2455.66067820557  Cost test:  2527.604149908669
Iteration :  1938  Cost train:  2455.6503446175266  Cost test:  2527.5941945953305
Iteration :  1939  Cost train:  2455.640015645245  Cost test:  2527.584244588146
Iteration :  1940  Cost train:  2455.629691282142  Cost test:  2527.574299879784
Iteration :  1941  Cost train:  2455.619371521648  Cost test:  2527.5643604629286
Iteration :  1942  Cost train:  2455.6090563572047  Cost test:  2527.5544263302736
Iteration :  1943  Cost train:  2455.5987457822644  Cost test:  2527.544497474526
Iteration :  1944  Cost train:  2455.588439790293  Cost test:  2527.534573888405
Iteration :  1945  Cost train:  2455.578138374765  Cost test:  2527.5246555646413
Iteration :  1946  Cost train:  2455.5678415291686  Cost test:  2527.51474249598
Iteration :  1947  Cost train:  2455.557549247004  Cost test:  2527.504834675177
Iteration :  1948  Cost train:  2455.547261521781  Cost test:  2527.494932095
Iteration :  1949  Cost train:  2455.536978347022  Cost test:  2527.4850347482297
Iteration :  1950  Cost train:  2455.52669971626  Cost test:  2527.47514262766
Iteration :  1951  Cost train:  2455.516425623041  Cost test:  2527.465255726094
Iteration :  1952  Cost train:  2455.506156060921  Cost test:  2527.45537403635
Iteration :  1953  Cost train:  2455.495891023468  Cost test:  2527.4454975512576
Iteration :  1954  Cost train:  2455.4856305042617  Cost test:  2527.4356262636566
Iteration :  1955  Cost train:  2455.475374496892  Cost test:  2527.4257601664026
Iteration :  1956  Cost train:  2455.4651229949613  Cost test:  2527.41589925236
Iteration :  1957  Cost train:  2455.454875992083  Cost test:  2527.406043514406
Iteration :  1958  Cost train:  2455.444633481881  Cost test:  2527.3961929454317
Iteration :  1959  Cost train:  2455.4343954579913  Cost test:  2527.3863475383373
Iteration :  1960  Cost train:  2455.4241619140607  Cost test:  2527.3765072860374
Iteration :  1961  Cost train:  2455.413932843749  Cost test:  2527.366672181457
Iteration :  1962  Cost train:  2455.403708240724  Cost test:  2527.356842217534
Iteration :  1963  Cost train:  2455.393488098667  Cost test:  2527.3470173872183
Iteration :  1964  Cost train:  2455.383272411271  Cost test:  2527.3371976834705
Iteration :  1965  Cost train:  2455.3730611722362  Cost test:  2527.327383099264
Iteration :  1966  Cost train:  2455.3628543752798  Cost test:  2527.3175736275844
Iteration :  1967  Cost train:  2455.352652014125  Cost test:  2527.307769261429
Iteration :  1968  Cost train:  2455.3424540825094  Cost test:  2527.2979699938055
Iteration :  1969  Cost train:  2455.3322605741805  Cost test:  2527.2881758177355
Iteration :  1970  Cost train:  2455.322071482895  Cost test:  2527.278386726251
Iteration :  1971  Cost train:  2455.311886802424  Cost test:  2527.268602712397
Iteration :  1972  Cost train:  2455.3017065265476  Cost test:  2527.258823769229
Iteration :  1973  Cost train:  2455.291530649057  Cost test:  2527.2490498898133
Iteration :  1974  Cost train:  2455.281359163756  Cost test:  2527.239281067231
Iteration :  1975  Cost train:  2455.2711920644556  Cost test:  2527.2295172945724
Iteration :  1976  Cost train:  2455.261029344982  Cost test:  2527.21975856494
Iteration :  1977  Cost train:  2455.2508709991703  Cost test:  2527.2100048714487
Iteration :  1978  Cost train:  2455.240717020866  Cost test:  2527.200256207224
Iteration :  1979  Cost train:  2455.2305674039267  Cost test:  2527.1905125654034
Iteration :  1980  Cost train:  2455.22042214222  Cost test:  2527.1807739391365
Iteration :  1981  Cost train:  2455.2102812296243  Cost test:  2527.1710403215834
Iteration :  1982  Cost train:  2455.2001446600298  Cost test:  2527.1613117059164
Iteration :  1983  Cost train:  2455.190012427336  Cost test:  2527.1515880853194
Iteration :  1984  Cost train:  2455.1798845254543  Cost test:  2527.1418694529875
Iteration :  1985  Cost train:  2455.169760948307  Cost test:  2527.132155802128
Iteration :  1986  Cost train:  2455.159641689826  Cost test:  2527.122447125958
Iteration :  1987  Cost train:  2455.149526743955  Cost test:  2527.1127434177074
Iteration :  1988  Cost train:  2455.139416104648  Cost test:  2527.1030446706177
Iteration :  1989  Cost train:  2455.129309765869  Cost test:  2527.0933508779403
Iteration :  1990  Cost train:  2455.119207721594  Cost test:  2527.08366203294
Iteration :  1991  Cost train:  2455.1091099658092  Cost test:  2527.0739781288917
Iteration :  1992  Cost train:  2455.09901649251  Cost test:  2527.064299159081
Iteration :  1993  Cost train:  2455.0889272957047  Cost test:  2527.0546251168066
Iteration :  1994  Cost train:  2455.0788423694103  Cost test:  2527.0449559953777
Iteration :  1995  Cost train:  2455.0687617076555  Cost test:  2527.0352917881137
Iteration :  1996  Cost train:  2455.058685304479  Cost test:  2527.025632488346
Iteration :  1997  Cost train:  2455.04861315393  Cost test:  2527.015978089419
Iteration :  1998  Cost train:  2455.0385452500686  Cost test:  2527.0063285846854
Iteration :  1999  Cost train:  2455.0284815869654  Cost test:  2526.9966839675108
Iteration :  2000  Cost train:  2455.018422158701  Cost test:  2526.9870442312713
Iteration :  2001  Cost train:  2455.008366959366  Cost test:  2526.9774093693554
Iteration :  2002  Cost train:  2454.998315983063  Cost test:  2526.967779375161
Iteration :  2003  Cost train:  2454.988269223904  Cost test:  2526.958154242098
Iteration :  2004  Cost train:  2454.9782266760108  Cost test:  2526.948533963587
Iteration :  2005  Cost train:  2454.968188333517  Cost test:  2526.9389185330606
Iteration :  2006  Cost train:  2454.9581541905654  Cost test:  2526.9293079439617
Iteration :  2007  Cost train:  2454.94812424131  Cost test:  2526.9197021897444
Iteration :  2008  Cost train:  2454.9380984799145  Cost test:  2526.9101012638735
Iteration :  2009  Cost train:  2454.9280769005522  Cost test:  2526.900505159825
Iteration :  2010  Cost train:  2454.918059497409  Cost test:  2526.890913871087
Iteration :  2011  Cost train:  2454.908046264678  Cost test:  2526.8813273911555
Iteration :  2012  Cost train:  2454.8980371965654  Cost test:  2526.8717457135417
Iteration :  2013  Cost train:  2454.888032287286  Cost test:  2526.8621688317644
Iteration :  2014  Cost train:  2454.878031531065  Cost test:  2526.8525967393552
Iteration :  2015  Cost train:  2454.8680349221386  Cost test:  2526.843029429854
Convergence Achieved at  2015.0  iteration
Cost Minima Found :  2454.8680349221386
Betas : 
X0              46.078514
T1               8.091378
RH_1            33.417666
T2              21.638912
RH_2           -13.930069
T3              12.726980
RH_3            18.977537
T4               5.763293
RH_4            12.698682
T5               1.389392
RH_5             0.138721
RH_6          -107.055190
T7               2.077176
RH_7           -21.212809
T8               7.655018
RH_8           -42.016563
RH_9           -16.087458
T_out           37.671893
Press_mm_hg     64.621670
RH_out        -161.935327
Windspeed       20.288474
Tdewpoint        1.977019
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
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Iteration :  3099  Cost train:  2426.7934131126162  Cost test:  2502.3053984821427
Iteration :  3100  Cost train:  2426.783332047339  Cost test:  2502.1922956495214
Iteration :  3101  Cost train:  2426.7732532451314  Cost test:  2502.2884124952434
Iteration :  3102  Cost train:  2426.7631767050825  Cost test:  2502.1757982198383
Iteration :  3103  Cost train:  2426.7531024262817  Cost test:  2502.271435835144
Iteration :  3104  Cost train:  2426.743030407822  Cost test:  2502.1593078720957
Iteration :  3105  Cost train:  2426.732960648795  Cost test:  2502.2544684888344
Iteration :  3106  Cost train:  2426.722893148296  Cost test:  2502.1428246036608
Iteration :  3107  Cost train:  2426.7128279054205  Cost test:  2502.2375104433513
Iteration :  3108  Cost train:  2426.7027649192637  Cost test:  2502.126348411901
Iteration :  3109  Cost train:  2426.692704188924  Cost test:  2502.220561685778
Iteration :  3110  Cost train:  2426.6826457135007  Cost test:  2502.10987929418
Iteration :  3111  Cost train:  2426.6725894920946  Cost test:  2502.2036222032452
Iteration :  3112  Cost train:  2426.662535523806  Cost test:  2502.093417247863
Iteration :  3113  Cost train:  2426.652483807739  Cost test:  2502.186691982929
Iteration :  3114  Cost train:  2426.6424343429953  Cost test:  2502.076962270311
Iteration :  3115  Cost train:  2426.6323871286822  Cost test:  2502.169771012051
Iteration :  3116  Cost train:  2426.6223421639047  Cost test:  2502.0605143588873
Iteration :  3117  Cost train:  2426.612299447771  Cost test:  2502.1528592778795
Iteration :  3118  Cost train:  2426.602258979389  Cost test:  2502.044073510951
Iteration :  3119  Cost train:  2426.5922207578687  Cost test:  2502.135956767727
Iteration :  3120  Cost train:  2426.5821847823213  Cost test:  2502.0276397238613
Iteration :  3121  Cost train:  2426.572151051859  Cost test:  2502.119063468952
Iteration :  3122  Cost train:  2426.5621195655945  Cost test:  2502.011212994975
Iteration :  3123  Cost train:  2426.5520903226434  Cost test:  2502.1021793689574
Iteration :  3124  Cost train:  2426.5420633221197  Cost test:  2501.9947933216486
Iteration :  3125  Cost train:  2426.5320385631426  Cost test:  2502.0853044551905
Iteration :  3126  Cost train:  2426.522016044828  Cost test:  2501.978380701237
Iteration :  3127  Cost train:  2426.511995766295  Cost test:  2502.068438715143
Iteration :  3128  Cost train:  2426.501977726665  Cost test:  2501.961975131092
Iteration :  3129  Cost train:  2426.4919619250586  Cost test:  2502.051582136352
Iteration :  3130  Cost train:  2426.4819483605984  Cost test:  2501.945576608565
Iteration :  3131  Cost train:  2426.4719370324083  Cost test:  2502.0347347063953
Iteration :  3132  Cost train:  2426.4619279396125  Cost test:  2501.9291851310068
Iteration :  3133  Cost train:  2426.451921081337  Cost test:  2502.0178964128977
Iteration :  3134  Cost train:  2426.441916456709  Cost test:  2501.912800695764
Iteration :  3135  Cost train:  2426.4319140648568  Cost test:  2502.0010672435246
Iteration :  3136  Cost train:  2426.421913904909  Cost test:  2501.8964233001843
Iteration :  3137  Cost train:  2426.411915975996  Cost test:  2501.9842471859865
Convergence Achieved at  3137.0  iteration
Cost Minima Found :  2426.411915975996
Betas : 
X0              50.915400
T1              14.514373
RH_1           107.184012
T2              51.290024
RH_2           -26.769808
T3              28.283545
RH_3            66.023806
T4               4.202032
RH_4            48.741698
T5              -5.829256
RH_5            12.517115
RH_6           -63.599637
T7              -8.030460
RH_7           -50.004085
T8              12.209429
RH_8          -107.811812
RH_9           -39.245345
T_out           80.359908
Press_mm_hg     73.482860
RH_out        -355.935002
Windspeed       58.198461
Tdewpoint        3.312146
dtype: float64

pd.concat([minima.groupby('Alpha')['Cost_test'].min(),minima.groupby('Alpha')['Iteration'].max()],axis=1)

import plotly.express as px
px.line(minima, x="Iteration", y="Cost_test", color="Alpha")

Determine best criteria(Experiment 2)¶

x=[0.001,0.005,0.01,0.05,0.1,0.5]
best_criteria=pd.DataFrame(columns=['Convergence_criteria','Cost_test','Iteration'])
for i in x:
    initial_params,params,graph=batch_gradient_descent_v3('lr',x_train,y_train,x_test,y_test,1,i,1000000)
    best_criteria=best_criteria.append(graph[['Convergence_criteria','Cost_test','Iteration']],ignore_index=True)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
Iteration :  109  Cost train:  4699.725151244447  Cost test:  4826.461334065434
Iteration :  110  Cost train:  4689.405032722035  Cost test:  4709.484461338859
Iteration :  111  Cost train:  4679.132531905506  Cost test:  4805.611038113325
Iteration :  112  Cost train:  4668.907428596511  Cost test:  4689.22026615031
Iteration :  113  Cost train:  4658.729503615403  Cost test:  4784.951528084699
Iteration :  114  Cost train:  4648.598538796419  Cost test:  4669.143727539292
Iteration :  115  Cost train:  4638.514316983173  Cost test:  4764.481049165222
Iteration :  116  Cost train:  4628.476622023865  Cost test:  4649.253109047221
Iteration :  117  Cost train:  4618.485238766649  Cost test:  4744.1978627137305
Iteration :  118  Cost train:  4608.539953055031  Cost test:  4629.54669026779
Iteration :  119  Cost train:  4598.640551723276  Cost test:  4724.100246112944
Iteration :  120  Cost train:  4588.786822591716  Cost test:  4610.022766698604
Iteration :  121  Cost train:  4578.978554462342  Cost test:  4704.186492621575
Iteration :  122  Cost train:  4569.215537114155  Cost test:  4590.679649594098
Iteration :  123  Cost train:  4559.497561298708  Cost test:  4684.454911227973
Iteration :  124  Cost train:  4549.824418735552  Cost test:  4571.515665820162
Iteration :  125  Cost train:  4540.195902107774  Cost test:  4664.903826504962
Iteration :  126  Cost train:  4530.611805057552  Cost test:  4552.529157709706
Iteration :  127  Cost train:  4521.071922181705  Cost test:  4645.531578465981
Iteration :  128  Cost train:  4511.576049027327  Cost test:  4533.718482919843
Iteration :  129  Cost train:  4502.123982087253  Cost test:  4626.336522422788
Iteration :  130  Cost train:  4492.715518795848  Cost test:  4515.082014290255
Iteration :  131  Cost train:  4483.350457524569  Cost test:  4607.317028844169
Iteration :  132  Cost train:  4474.028597577596  Cost test:  4496.618139702992
Iteration :  133  Cost train:  4464.749739187557  Cost test:  4588.471483216195
Iteration :  134  Cost train:  4455.5136835112735  Cost test:  4478.3252619432815
Iteration :  135  Cost train:  4446.320232625415  Cost test:  4569.798285903653
Iteration :  136  Cost train:  4437.1691895221975  Cost test:  4460.2017985620105
Iteration :  137  Cost train:  4428.060358105327  Cost test:  4551.2958520126285
Iteration :  138  Cost train:  4418.993543185645  Cost test:  4442.246181739165
Iteration :  139  Cost train:  4409.9685504769395  Cost test:  4532.962611254896
Iteration :  140  Cost train:  4400.985186591761  Cost test:  4424.456858148827
Iteration :  141  Cost train:  4392.043259037327  Cost test:  4514.797007812767
Iteration :  142  Cost train:  4383.14257621131  Cost test:  4406.832288825022
Iteration :  143  Cost train:  4374.282947397772  Cost test:  4496.797500205778
Iteration :  144  Cost train:  4365.464182762994  Cost test:  4389.370949029123
Iteration :  145  Cost train:  4356.686093351576  Cost test:  4478.962561158386
Iteration :  146  Cost train:  4347.948491082074  Cost test:  4372.071328118565
Iteration :  147  Cost train:  4339.251188743211  Cost test:  4461.290677469036
Iteration :  148  Cost train:  4330.593999989701  Cost test:  4354.9319294162615
Iteration :  149  Cost train:  4321.976739338369  Cost test:  4443.7803498800995
Iteration :  150  Cost train:  4313.39922216397  Cost test:  4337.951270081756
Iteration :  151  Cost train:  4304.861264695496  Cost test:  4426.430092949308
Iteration :  152  Cost train:  4296.362684011985  Cost test:  4321.127880983369
Iteration :  153  Cost train:  4287.9032980386655  Cost test:  4409.238434922531
Iteration :  154  Cost train:  4279.482925543058  Cost test:  4304.4603065714955
Iteration :  155  Cost train:  4271.101386131102  Cost test:  4392.203917607198
Iteration :  156  Cost train:  4262.758500243201  Cost test:  4287.947104753167
Iteration :  157  Cost train:  4254.45408915037  Cost test:  4375.325096247385
Iteration :  158  Cost train:  4246.187974950504  Cost test:  4271.58684676754
Iteration :  159  Cost train:  4237.959980564389  Cost test:  4358.600539399739
Iteration :  160  Cost train:  4229.76992973207  Cost test:  4255.378117062906
Iteration :  161  Cost train:  4221.617647008818  Cost test:  4342.028828810755
Iteration :  162  Cost train:  4213.502957761666  Cost test:  4239.31951317443
Iteration :  163  Cost train:  4205.425688165381  Cost test:  4325.608559295011
Iteration :  164  Cost train:  4197.385665198889  Cost test:  4223.409645603407
Iteration :  165  Cost train:  4189.382716641492  Cost test:  4309.338338614689
Iteration :  166  Cost train:  4181.41667106918  Cost test:  4207.647137697362
Iteration :  167  Cost train:  4173.487357850935  Cost test:  4293.216787360164
Iteration :  168  Cost train:  4165.594607145094  Cost test:  4192.030625531408
Iteration :  169  Cost train:  4157.7382498956  Cost test:  4277.242538831643
Iteration :  170  Cost train:  4149.918117828452  Cost test:  4176.558757790474
Iteration :  171  Cost train:  4142.134043448153  Cost test:  4261.414238921733
Iteration :  172  Cost train:  4134.385860033964  Cost test:  4161.230195653035
Iteration :  173  Cost train:  4126.673401636381  Cost test:  4245.730545999699
Iteration :  174  Cost train:  4118.996503073542  Cost test:  4146.043612675481
Iteration :  175  Cost train:  4111.354999927696  Cost test:  4230.19013079586
Iteration :  176  Cost train:  4103.7487285417355  Cost test:  4130.997694677668
Iteration :  177  Cost train:  4096.177526015566  Cost test:  4214.79167628794
Iteration :  178  Cost train:  4088.6412302026342  Cost test:  4116.091139629881
Iteration :  179  Cost train:  4081.139679706506  Cost test:  4199.533877587954
Iteration :  180  Cost train:  4073.6727138772994  Cost test:  4101.322657540359
Iteration :  181  Cost train:  4066.2401728082496  Cost test:  4184.415441830289
Iteration :  182  Cost train:  4058.841897332368  Cost test:  4086.6909703439896
Iteration :  183  Cost train:  4051.477729018931  Cost test:  4169.435088060791
Iteration :  184  Cost train:  4044.1475101700757  Cost test:  4072.194811792403
Iteration :  185  Cost train:  4036.851083817411  Cost test:  4154.5915471270055
Iteration :  186  Cost train:  4029.5882937186657  Cost test:  4057.8329273444688
Iteration :  187  Cost train:  4022.358984354287  Cost test:  4139.883561569078
Iteration :  188  Cost train:  4015.16300092415  Cost test:  4043.6040740581475
Iteration :  189  Cost train:  4008.0001893442627  Cost test:  4125.309885512046
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Iteration :  1991  Cost train:  2439.8581617835407  Cost test:  2514.01489076402
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Iteration :  2007  Cost train:  2439.623774285107  Cost test:  2513.784706806051
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Iteration :  2010  Cost train:  2439.5801308034006  Cost test:  2512.4329454949107
Iteration :  2011  Cost train:  2439.5656038497236  Cost test:  2513.727735392472
Iteration :  2012  Cost train:  2439.551087275206  Cost test:  2512.4105705975444
Iteration :  2013  Cost train:  2439.53658104551  Cost test:  2513.6993339231435
Iteration :  2014  Cost train:  2439.5220851264485  Cost test:  2512.3882235685023
Iteration :  2015  Cost train:  2439.5075994839895  Cost test:  2513.670988151017
Iteration :  2016  Cost train:  2439.4931240842516  Cost test:  2512.365904193517
Iteration :  2017  Cost train:  2439.4786588935062  Cost test:  2513.6426977337333
Iteration :  2018  Cost train:  2439.464203878176  Cost test:  2512.3436122604817
Iteration :  2019  Cost train:  2439.4497590048313  Cost test:  2513.614462331681
Iteration :  2020  Cost train:  2439.4353242401953  Cost test:  2512.321347559431
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Iteration :  25671  Cost train:  2346.1838253262436  Cost test:  2431.716145744389
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Iteration :  27764  Cost train:  2341.915853721107  Cost test:  2427.414238806323
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Iteration :  27791  Cost train:  2341.8618931618594  Cost test:  2427.3596191368933
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Iteration :  27812  Cost train:  2341.819942708932  Cost test:  2427.3171525240923
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Iteration :  27815  Cost train:  2341.813951134297  Cost test:  2427.3110869615975
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Iteration :  28582  Cost train:  2340.2930672011084  Cost test:  2425.769303598012
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Iteration :  29401  Cost train:  2338.692805387815  Cost test:  2424.1426699590984
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Iteration :  29435  Cost train:  2338.626893696974  Cost test:  2424.0755794909996
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Iteration :  29448  Cost train:  2338.6017030683083  Cost test:  2424.0499364539232
Iteration :  29449  Cost train:  2338.5997655772885  Cost test:  2424.047964123403
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Iteration :  29470  Cost train:  2338.5590865015497  Cost test:  2424.006552138001
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Iteration :  29485  Cost train:  2338.530039641677  Cost test:  2423.9769802775027
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Iteration :  29517  Cost train:  2338.46809979163  Cost test:  2423.9139162787915
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Iteration :  29519  Cost train:  2338.464229761445  Cost test:  2423.9099758022244
Iteration :  29520  Cost train:  2338.4622947997377  Cost test:  2423.9080056090856
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Iteration :  29522  Cost train:  2338.4584249830873  Cost test:  2423.904065313093
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Iteration :  29526  Cost train:  2338.450685776815  Cost test:  2423.8961850822475
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Iteration :  29634  Cost train:  2338.241942203328  Cost test:  2423.6836008098776
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Iteration :  34612  Cost train:  2329.0510109746037  Cost test:  2414.2600976297554
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Iteration :  34769  Cost train:  2328.77426461795  Cost test:  2413.9746193747364
Iteration :  34770  Cost train:  2328.772504369462  Cost test:  2413.9728032945095
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Iteration :  35506  Cost train:  2327.485372981057  Cost test:  2412.643871767581
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Iteration :  35703  Cost train:  2327.1436851838394  Cost test:  2412.290765478482
Iteration :  35704  Cost train:  2327.141953754447  Cost test:  2412.2889758494644
Iteration :  35705  Cost train:  2327.1402223555783  Cost test:  2412.2871862485895
Iteration :  35706  Cost train:  2327.1384909872318  Cost test:  2412.2853966758576
Iteration :  35707  Cost train:  2327.1367596494074  Cost test:  2412.283607131268
Iteration :  35708  Cost train:  2327.1350283421048  Cost test:  2412.2818176148203
Iteration :  35709  Cost train:  2327.133297065322  Cost test:  2412.2800281265145
Iteration :  35710  Cost train:  2327.1315658190592  Cost test:  2412.2782386663494
Iteration :  35711  Cost train:  2327.129834603316  Cost test:  2412.276449234326
Iteration :  35712  Cost train:  2327.1281034180906  Cost test:  2412.2746598304425
Iteration :  35713  Cost train:  2327.126372263383  Cost test:  2412.2728704546994
Iteration :  35714  Cost train:  2327.124641139193  Cost test:  2412.2710811070956
Iteration :  35715  Cost train:  2327.1229100455184  Cost test:  2412.2692917876316
Iteration :  35716  Cost train:  2327.1211789823606  Cost test:  2412.2675024963064
Iteration :  35717  Cost train:  2327.1194479497167  Cost test:  2412.2657132331196
Iteration :  35718  Cost train:  2327.1177169475873  Cost test:  2412.2639239980713
Iteration :  35719  Cost train:  2327.115985975972  Cost test:  2412.262134791161
Iteration :  35720  Cost train:  2327.1142550348695  Cost test:  2412.2603456123875
Iteration :  35721  Cost train:  2327.1125241242785  Cost test:  2412.258556461751
Iteration :  35722  Cost train:  2327.1107932441996  Cost test:  2412.256767339252
Iteration :  35723  Cost train:  2327.109062394631  Cost test:  2412.254978244888
Iteration :  35724  Cost train:  2327.107331575572  Cost test:  2412.2531891786607
Iteration :  35725  Cost train:  2327.105600787023  Cost test:  2412.251400140569
Iteration :  35726  Cost train:  2327.1038700289823  Cost test:  2412.2496111306123
Iteration :  35727  Cost train:  2327.1021393014494  Cost test:  2412.2478221487904
Iteration :  35728  Cost train:  2327.100408604424  Cost test:  2412.2460331951024
Iteration :  35729  Cost train:  2327.098677937905  Cost test:  2412.2442442695483
Iteration :  35730  Cost train:  2327.096947301892  Cost test:  2412.2424553721285
Iteration :  35731  Cost train:  2327.095216696384  Cost test:  2412.240666502841
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Iteration :  35734  Cost train:  2327.0900250628833  Cost test:  2412.2353000637754
Iteration :  35735  Cost train:  2327.088294579389  Cost test:  2412.2335113070176
Iteration :  35736  Cost train:  2327.0865641263954  Cost test:  2412.2317225783904
Iteration :  35737  Cost train:  2327.0848337039038  Cost test:  2412.229933877894
Iteration :  35738  Cost train:  2327.0831033119116  Cost test:  2412.228145205529
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Iteration :  35740  Cost train:  2327.0796426194256  Cost test:  2412.2245679451876
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Iteration :  35742  Cost train:  2327.076182048932  Cost test:  2412.220990797364
Iteration :  35743  Cost train:  2327.0744518094307  Cost test:  2412.219202265645
Iteration :  35744  Cost train:  2327.072721600425  Cost test:  2412.217413762054
Iteration :  35745  Cost train:  2327.070991421915  Cost test:  2412.215625286591
Iteration :  35746  Cost train:  2327.0692612738994  Cost test:  2412.2138368392552
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Iteration :  35748  Cost train:  2327.0658010693496  Cost test:  2412.2102600289654
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Iteration :  35750  Cost train:  2327.0623409867694  Cost test:  2412.20668333118
Iteration :  35751  Cost train:  2327.060610991216  Cost test:  2412.204895024476
Iteration :  35752  Cost train:  2327.058881026154  Cost test:  2412.2031067458975
Iteration :  35753  Cost train:  2327.057151091581  Cost test:  2412.2013184954426
Iteration :  35754  Cost train:  2327.055421187497  Cost test:  2412.199530273113
Iteration :  35755  Cost train:  2327.053691313901  Cost test:  2412.1977420789062
Iteration :  35756  Cost train:  2327.051961470793  Cost test:  2412.1959539128243
Iteration :  35757  Cost train:  2327.0502316581715  Cost test:  2412.1941657748644
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Iteration :  35760  Cost train:  2327.045042403222  Cost test:  2412.188801529722
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Iteration :  35762  Cost train:  2327.041583052344  Cost test:  2412.1852255069016
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Iteration :  35770  Cost train:  2327.027746868083  Cost test:  2412.1709225404265
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Iteration :  35781  Cost train:  2327.0087252995054  Cost test:  2412.151258899791
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Iteration :  35783  Cost train:  2327.0052672286206  Cost test:  2412.147684057894
Iteration :  35784  Cost train:  2327.003538238881  Cost test:  2412.1458966791147
Iteration :  35785  Cost train:  2327.0018092796076  Cost test:  2412.1441093284475
Iteration :  35786  Cost train:  2327.000080350802  Cost test:  2412.1423220058928
Iteration :  35787  Cost train:  2326.998351452461  Cost test:  2412.140534711449
Iteration :  35788  Cost train:  2326.996622584586  Cost test:  2412.1387474451176
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Iteration :  35791  Cost train:  2326.9914361637443  Cost test:  2412.133385814785
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Iteration :  35811  Cost train:  2326.956867030236  Cost test:  2412.097648077293
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Iteration :  35820  Cost train:  2326.9413148940066  Cost test:  2412.081569762913
Iteration :  35821  Cost train:  2326.93958703109  Cost test:  2412.0797834240357
Iteration :  35822  Cost train:  2326.937859198614  Cost test:  2412.0779971132556
Iteration :  35823  Cost train:  2326.93613139658  Cost test:  2412.076210830574
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Iteration :  35825  Cost train:  2326.93267588383  Cost test:  2412.072638349501
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Iteration :  35827  Cost train:  2326.9292204928342  Cost test:  2412.069065980815
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Iteration :  35830  Cost train:  2326.924037634618  Cost test:  2412.0637076385033
Iteration :  35831  Cost train:  2326.9223100760837  Cost test:  2412.0619215805887
Iteration :  35832  Cost train:  2326.920582547984  Cost test:  2412.060135550769
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Iteration :  35836  Cost train:  2326.913672739914  Cost test:  2412.0529917124236
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Iteration :  35839  Cost train:  2326.9084907033894  Cost test:  2412.0476341286353
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Iteration :  35864  Cost train:  2326.8653177139777  Cost test:  2412.0029974279796
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Iteration :  35925  Cost train:  2326.7600553668835  Cost test:  2411.8941575239337
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Iteration :  35936  Cost train:  2326.741085662824  Cost test:  2411.874541769462
Iteration :  35937  Cost train:  2326.739361326454  Cost test:  2411.8727586873847
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Iteration :  35939  Cost train:  2326.7359127447958  Cost test:  2411.8691926073893
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Iteration :  36871  Cost train:  2325.141994217795  Cost test:  2410.2195561488725
Iteration :  36872  Cost train:  2325.140297968052  Cost test:  2410.217799125081
Iteration :  36873  Cost train:  2325.1386017480304  Cost test:  2410.2160421289736
Iteration :  36874  Cost train:  2325.1369055577293  Cost test:  2410.21428516055
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Iteration :  36881  Cost train:  2325.125033057724  Cost test:  2410.20198715669
Iteration :  36882  Cost train:  2325.123337105159  Cost test:  2410.2002304097205
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Iteration :  36891  Cost train:  2325.1080748691224  Cost test:  2410.1844209325423
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Iteration :  36893  Cost train:  2325.1046835879188  Cost test:  2410.1809080198423
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Iteration :  36928  Cost train:  2325.0453553971033  Cost test:  2410.1194499646294
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Iteration :  36930  Cost train:  2325.0419663133184  Cost test:  2410.115939099398
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Iteration :  36932  Cost train:  2325.038577348261  Cost test:  2410.1124283448094
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Iteration :  36987  Cost train:  2324.9454273146207  Cost test:  2410.0159259393113
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Iteration :  37390  Cost train:  2324.265620172636  Cost test:  2409.31137277154
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Iteration :  37415  Cost train:  2324.2236061183166  Cost test:  2409.267813261301
Iteration :  37416  Cost train:  2324.2219259378753  Cost test:  2409.266071237969
Iteration :  37417  Cost train:  2324.220245786792  Cost test:  2409.2643292420994
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Iteration :  37419  Cost train:  2324.2168855726973  Cost test:  2409.260845332751
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Iteration :  37421  Cost train:  2324.2135254760265  Cost test:  2409.257361533253
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Iteration :  37570  Cost train:  2323.9635281362907  Cost test:  2408.9981271761912
Iteration :  37571  Cost train:  2323.9618524984717  Cost test:  2408.996389404866
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Iteration :  37575  Cost train:  2323.955150239746  Cost test:  2408.9894385935654
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Iteration :  37604  Cost train:  2323.9065728590444  Cost test:  2408.939058320301
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Iteration :  37606  Cost train:  2323.9032236013013  Cost test:  2408.935584667804
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Iteration :  37608  Cost train:  2323.89987446049  Cost test:  2408.932111124851
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Iteration :  37610  Cost train:  2323.8965254366053  Cost test:  2408.9286376914383
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Iteration :  37613  Cost train:  2323.8915021200028  Cost test:  2408.923427746702
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Iteration :  37620  Cost train:  2323.879782070891  Cost test:  2408.9112721673755
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Iteration :  37640  Cost train:  2323.8463041059163  Cost test:  2408.8765493329283
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Iteration :  37688  Cost train:  2323.7660046516567  Cost test:  2408.793259195249
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Iteration :  37694  Cost train:  2323.7559719483784  Cost test:  2408.782852360055
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Iteration :  37717  Cost train:  2323.717522981168  Cost test:  2408.742968612228
Iteration :  37718  Cost train:  2323.715851636921  Cost test:  2408.7412348643575
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Iteration :  37720  Cost train:  2323.712509035904  Cost test:  2408.737767450635
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Iteration :  37722  Cost train:  2323.7091665515204  Cost test:  2408.73430014627
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Iteration :  37730  Cost train:  2323.695797780208  Cost test:  2408.7204320223113
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Iteration :  37802  Cost train:  2323.5755627549756  Cost test:  2408.5956976064676
Iteration :  37803  Cost train:  2323.573893886952  Cost test:  2408.5939661810307
Iteration :  37804  Cost train:  2323.572225048032  Cost test:  2408.5922347828973
Iteration :  37805  Cost train:  2323.5705562382163  Cost test:  2408.59050341207
Iteration :  37806  Cost train:  2323.5688874575026  Cost test:  2408.588772068546
Iteration :  37807  Cost train:  2323.5672187058913  Cost test:  2408.587040752326
Iteration :  37808  Cost train:  2323.565549983381  Cost test:  2408.585309463409
Iteration :  37809  Cost train:  2323.5638812899715  Cost test:  2408.5835782017953
Iteration :  37810  Cost train:  2323.5622126256617  Cost test:  2408.581846967484
Iteration :  37811  Cost train:  2323.5605439904516  Cost test:  2408.5801157604756
Iteration :  37812  Cost train:  2323.5588753843404  Cost test:  2408.5783845807678
Iteration :  37813  Cost train:  2323.557206807327  Cost test:  2408.576653428362
Iteration :  37814  Cost train:  2323.555538259411  Cost test:  2408.574922303257
Iteration :  37815  Cost train:  2323.5538697405923  Cost test:  2408.5731912054525
Iteration :  37816  Cost train:  2323.5522012508695  Cost test:  2408.571460134948
Iteration :  37817  Cost train:  2323.5505327902424  Cost test:  2408.5697290917433
Iteration :  37818  Cost train:  2323.548864358709  Cost test:  2408.5679980758377
Iteration :  37819  Cost train:  2323.547195956271  Cost test:  2408.566267087231
Iteration :  37820  Cost train:  2323.5455275829268  Cost test:  2408.5645361259226
Iteration :  37821  Cost train:  2323.5438592386745  Cost test:  2408.562805191913
Iteration :  37822  Cost train:  2323.5421909235147  Cost test:  2408.5610742852
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Iteration :  37824  Cost train:  2323.5388543804693  Cost test:  2408.557612553666
Iteration :  37825  Cost train:  2323.5371861525823  Cost test:  2408.555881728844
Iteration :  37826  Cost train:  2323.535517953785  Cost test:  2408.554150931317
Iteration :  37827  Cost train:  2323.533849784077  Cost test:  2408.5524201610865
Iteration :  37828  Cost train:  2323.532181643457  Cost test:  2408.550689418151
Iteration :  37829  Cost train:  2323.5305135319245  Cost test:  2408.54895870251
Iteration :  37830  Cost train:  2323.5288454494794  Cost test:  2408.547228014163
Iteration :  37831  Cost train:  2323.52717739612  Cost test:  2408.545497353111
Iteration :  37832  Cost train:  2323.5255093718465  Cost test:  2408.5437667193514
Iteration :  37833  Cost train:  2323.5238413766588  Cost test:  2408.5420361128854
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Iteration :  37835  Cost train:  2323.5205054735347  Cost test:  2408.5385749818306
Iteration :  37836  Cost train:  2323.518837565598  Cost test:  2408.5368444572405
Iteration :  37837  Cost train:  2323.5171696867437  Cost test:  2408.535113959943
Iteration :  37838  Cost train:  2323.5155018369705  Cost test:  2408.5333834899357
Iteration :  37839  Cost train:  2323.5138340162794  Cost test:  2408.5316530472196
Iteration :  37840  Cost train:  2323.5121662246684  Cost test:  2408.529922631793
Iteration :  37841  Cost train:  2323.510498462137  Cost test:  2408.5281922436566
Iteration :  37842  Cost train:  2323.508830728685  Cost test:  2408.5264618828096
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Iteration :  37846  Cost train:  2323.5021600856558  Cost test:  2408.519540712306
Iteration :  37847  Cost train:  2323.50049249759  Cost test:  2408.5178104878996
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Iteration :  37849  Cost train:  2323.4971574086835  Cost test:  2408.514350120947
Iteration :  37850  Cost train:  2323.4954899078416  Cost test:  2408.5126199783995
Iteration :  37851  Cost train:  2323.493822436073  Cost test:  2408.5108898631383
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Iteration :  37856  Cost train:  2323.4854855133076  Cost test:  2408.5022396961003
Iteration :  37857  Cost train:  2323.4838182159656  Cost test:  2408.500509744544
Iteration :  37858  Cost train:  2323.482150947692  Cost test:  2408.4987798202706
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Iteration :  37861  Cost train:  2323.477149317277  Cost test:  2408.493590211143
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Iteration :  37864  Cost train:  2323.4721479484588  Cost test:  2408.4884008475437
Iteration :  37865  Cost train:  2323.470480883648  Cost test:  2408.486671114238
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Iteration :  37868  Cost train:  2323.465479863596  Cost test:  2408.481482077995
Iteration :  37869  Cost train:  2323.463812915036  Cost test:  2408.479752453805
Iteration :  37870  Cost train:  2323.462145995537  Cost test:  2408.478022856892
Iteration :  37871  Cost train:  2323.4604791050983  Cost test:  2408.4762932872572
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Iteration :  37885  Cost train:  2323.4371456899244  Cost test:  2408.4520821762553
Iteration :  37886  Cost train:  2323.435479235312  Cost test:  2408.4503530157313
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Iteration :  37891  Cost train:  2323.4271473979866  Cost test:  2408.441707622164
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Iteration :  37901  Cost train:  2323.410485901753  Cost test:  2408.42441888013
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Iteration :  37903  Cost train:  2323.4071539510087  Cost test:  2408.4209614589113
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Iteration :  37906  Cost train:  2323.402156242682  Cost test:  2408.41577553156
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Iteration :  37912  Cost train:  2323.392161610007  Cost test:  2408.4054044129352
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Iteration :  37916  Cost train:  2323.3854991022254  Cost test:  2408.398490879058
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Iteration :  37918  Cost train:  2323.3821680225196  Cost test:  2408.3950342756716
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Iteration :  37920  Cost train:  2323.37883705893  Cost test:  2408.3915777813145
Iteration :  37921  Cost train:  2323.3771716206775  Cost test:  2408.3898495750223
Iteration :  37922  Cost train:  2323.3755062114515  Cost test:  2408.388121395985
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Iteration :  37925  Cost train:  2323.370510157931  Cost test:  2408.3829370224094
Iteration :  37926  Cost train:  2323.3688448648077  Cost test:  2408.3812089523935
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Iteration :  37929  Cost train:  2323.363849159578  Cost test:  2408.376024905871
Iteration :  37930  Cost train:  2323.362183982546  Cost test:  2408.3742969448695
Iteration :  37931  Cost train:  2323.3605188345355  Cost test:  2408.3725690111214
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Iteration :  37933  Cost train:  2323.3571886255754  Cost test:  2408.3691132253803
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Iteration :  37936  Cost train:  2323.352193529779  Cost test:  2408.363929751153
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Iteration :  37940  Cost train:  2323.3455338082913  Cost test:  2408.357018833683
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Iteration :  37942  Cost train:  2323.342204121638  Cost test:  2408.35356353844
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Iteration :  37956  Cost train:  2323.3188995642913  Cost test:  2408.3293795232903
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Iteration :  37958  Cost train:  2323.315570805925  Cost test:  2408.3259250998785
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Iteration :  37960  Cost train:  2323.312242163571  Cost test:  2408.322470785431
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Iteration :  38036  Cost train:  2323.1858396680764  Cost test:  2408.1912875460343
Iteration :  38037  Cost train:  2323.1841775926428  Cost test:  2408.189562498713
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Iteration :  38269  Cost train:  2322.7993572590312  Cost test:  2407.790086041232
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Iteration :  38281  Cost train:  2322.779494994633  Cost test:  2407.7694632022412
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Iteration :  38325  Cost train:  2322.70670215827  Cost test:  2407.693879516055
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Iteration :  38393  Cost train:  2322.5943136609485  Cost test:  2407.5771715047954
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Iteration :  38502  Cost train:  2322.4144385002196  Cost test:  2407.3903564075567
Iteration :  38503  Cost train:  2322.412789846569  Cost test:  2407.3886439942057
Iteration :  38504  Cost train:  2322.411141221571  Cost test:  2407.386931607868
Iteration :  38505  Cost train:  2322.409492625225  Cost test:  2407.3852192485447
Iteration :  38506  Cost train:  2322.4078440575304  Cost test:  2407.3835069162333
Iteration :  38507  Cost train:  2322.4061955184857  Cost test:  2407.3817946109357
Iteration :  38508  Cost train:  2322.4045470080914  Cost test:  2407.38008233265
Iteration :  38509  Cost train:  2322.4028985263462  Cost test:  2407.3783700813765
Iteration :  38510  Cost train:  2322.4012500732492  Cost test:  2407.3766578571144
Iteration :  38511  Cost train:  2322.3996016488004  Cost test:  2407.3749456598634
Iteration :  38512  Cost train:  2322.397953252999  Cost test:  2407.3732334896226
Iteration :  38513  Cost train:  2322.396304885844  Cost test:  2407.3715213463934
Iteration :  38514  Cost train:  2322.394656547335  Cost test:  2407.3698092301725
Iteration :  38515  Cost train:  2322.393008237472  Cost test:  2407.3680971409617
Iteration :  38516  Cost train:  2322.3913599562534  Cost test:  2407.36638507876
Iteration :  38517  Cost train:  2322.389711703679  Cost test:  2407.3646730435667
Iteration :  38518  Cost train:  2322.3880634797483  Cost test:  2407.362961035381
Iteration :  38519  Cost train:  2322.3864152844594  Cost test:  2407.3612490542037
Iteration :  38520  Cost train:  2322.3847671178137  Cost test:  2407.3595371000333
Iteration :  38521  Cost train:  2322.3831189798098  Cost test:  2407.3578251728704
Iteration :  38522  Cost train:  2322.381470870446  Cost test:  2407.356113272713
Iteration :  38523  Cost train:  2322.3798227897228  Cost test:  2407.354401399563
Iteration :  38524  Cost train:  2322.3781747376397  Cost test:  2407.3526895534173
Iteration :  38525  Cost train:  2322.3765267141944  Cost test:  2407.350977734278
Iteration :  38526  Cost train:  2322.374878719389  Cost test:  2407.3492659421427
Iteration :  38527  Cost train:  2322.3732307532205  Cost test:  2407.347554177012
Iteration :  38528  Cost train:  2322.3715828156896  Cost test:  2407.345842438885
Iteration :  38529  Cost train:  2322.3699349067942  Cost test:  2407.344130727762
Iteration :  38530  Cost train:  2322.368287026535  Cost test:  2407.342419043642
Iteration :  38531  Cost train:  2322.366639174912  Cost test:  2407.3407073865246
Iteration :  38532  Cost train:  2322.364991351923  Cost test:  2407.3389957564095
Iteration :  38533  Cost train:  2322.363343557567  Cost test:  2407.3372841532964
Iteration :  38534  Cost train:  2322.3616957918452  Cost test:  2407.335572577185
Iteration :  38535  Cost train:  2322.360048054756  Cost test:  2407.3338610280744
Iteration :  38536  Cost train:  2322.358400346299  Cost test:  2407.3321495059636
Iteration :  38537  Cost train:  2322.3567526664733  Cost test:  2407.3304380108543
Iteration :  38538  Cost train:  2322.355105015278  Cost test:  2407.328726542744
Iteration :  38539  Cost train:  2322.3534573927127  Cost test:  2407.327015101633
Iteration :  38540  Cost train:  2322.3518097987767  Cost test:  2407.325303687521
Iteration :  38541  Cost train:  2322.3501622334697  Cost test:  2407.3235923004077
Iteration :  38542  Cost train:  2322.348514696791  Cost test:  2407.321880940292
Iteration :  38543  Cost train:  2322.3468671887404  Cost test:  2407.320169607175
Iteration :  38544  Cost train:  2322.345219709316  Cost test:  2407.3184583010543
Iteration :  38545  Cost train:  2322.343572258518  Cost test:  2407.3167470219314
Iteration :  38546  Cost train:  2322.3419248363457  Cost test:  2407.3150357698037
Iteration :  38547  Cost train:  2322.340277442798  Cost test:  2407.313324544673
Iteration :  38548  Cost train:  2322.3386300778757  Cost test:  2407.311613346537
Iteration :  38549  Cost train:  2322.3369827415763  Cost test:  2407.309902175397
Iteration :  38550  Cost train:  2322.3353354339  Cost test:  2407.308191031251
Iteration :  38551  Cost train:  2322.3336881548466  Cost test:  2407.3064799141002
Iteration :  38552  Cost train:  2322.332040904415  Cost test:  2407.304768823942
Iteration :  38553  Cost train:  2322.330393682604  Cost test:  2407.3030577607788
Iteration :  38554  Cost train:  2322.3287464894142  Cost test:  2407.3013467246074
Iteration :  38555  Cost train:  2322.327099324844  Cost test:  2407.2996357154298
Iteration :  38556  Cost train:  2322.325452188893  Cost test:  2407.2979247332432
Iteration :  38557  Cost train:  2322.3238050815603  Cost test:  2407.296213778049
Iteration :  38558  Cost train:  2322.322158002846  Cost test:  2407.294502849846
Iteration :  38559  Cost train:  2322.320510952749  Cost test:  2407.292791948634
Iteration :  38560  Cost train:  2322.318863931269  Cost test:  2407.2910810744124
Iteration :  38561  Cost train:  2322.3172169384047  Cost test:  2407.2893702271817
Iteration :  38562  Cost train:  2322.315569974156  Cost test:  2407.28765940694
Iteration :  38563  Cost train:  2322.313923038522  Cost test:  2407.285948613688
Iteration :  38564  Cost train:  2322.312276131502  Cost test:  2407.2842378474243
Iteration :  38565  Cost train:  2322.310629253096  Cost test:  2407.2825271081497
Iteration :  38566  Cost train:  2322.3089824033027  Cost test:  2407.2808163958625
Iteration :  38567  Cost train:  2322.3073355821216  Cost test:  2407.2791057105633
Iteration :  38568  Cost train:  2322.305688789552  Cost test:  2407.2773950522514
Iteration :  38569  Cost train:  2322.304042025594  Cost test:  2407.275684420926
Iteration :  38570  Cost train:  2322.302395290245  Cost test:  2407.273973816587
Iteration :  38571  Cost train:  2322.300748583507  Cost test:  2407.272263239234
Iteration :  38572  Cost train:  2322.299101905378  Cost test:  2407.2705526888667
Iteration :  38573  Cost train:  2322.297455255857  Cost test:  2407.2688421654843
Iteration :  38574  Cost train:  2322.2958086349436  Cost test:  2407.267131669086
Iteration :  38575  Cost train:  2322.2941620426373  Cost test:  2407.265421199673
Iteration :  38576  Cost train:  2322.2925154789386  Cost test:  2407.2637107572427
Iteration :  38577  Cost train:  2322.290868943845  Cost test:  2407.2620003417965
Iteration :  38578  Cost train:  2322.289222437357  Cost test:  2407.260289953333
Iteration :  38579  Cost train:  2322.287575959473  Cost test:  2407.258579591852
Iteration :  38580  Cost train:  2322.2859295101935  Cost test:  2407.2568692573536
Iteration :  38581  Cost train:  2322.2842830895174  Cost test:  2407.2551589498376
Iteration :  38582  Cost train:  2322.2826366974436  Cost test:  2407.2534486693016
Iteration :  38583  Cost train:  2322.280990333972  Cost test:  2407.2517384157472
Iteration :  38584  Cost train:  2322.279343999102  Cost test:  2407.250028189173
Iteration :  38585  Cost train:  2322.2776976928326  Cost test:  2407.248317989579
Iteration :  38586  Cost train:  2322.2760514151637  Cost test:  2407.246607816964
Iteration :  38587  Cost train:  2322.274405166094  Cost test:  2407.244897671329
Iteration :  38588  Cost train:  2322.2727589456235  Cost test:  2407.243187552672
Iteration :  38589  Cost train:  2322.2711127537514  Cost test:  2407.2414774609942
Iteration :  38590  Cost train:  2322.269466590476  Cost test:  2407.239767396294
Iteration :  38591  Cost train:  2322.2678204557983  Cost test:  2407.2380573585715
Iteration :  38592  Cost train:  2322.266174349717  Cost test:  2407.236347347826
Iteration :  38593  Cost train:  2322.2645282722315  Cost test:  2407.234637364057
Iteration :  38594  Cost train:  2322.2628822233405  Cost test:  2407.2329274072645
Iteration :  38595  Cost train:  2322.2612362030445  Cost test:  2407.231217477448
Iteration :  38596  Cost train:  2322.2595902113417  Cost test:  2407.2295075746065
Iteration :  38597  Cost train:  2322.2579442482324  Cost test:  2407.2277976987402
Iteration :  38598  Cost train:  2322.256298313716  Cost test:  2407.226087849849
Iteration :  38599  Cost train:  2322.254652407791  Cost test:  2407.2243780279314
Iteration :  38600  Cost train:  2322.2530065304577  Cost test:  2407.2226682329874
Iteration :  38601  Cost train:  2322.2513606817147  Cost test:  2407.2209584650172
Iteration :  38602  Cost train:  2322.2497148615616  Cost test:  2407.2192487240195
Iteration :  38603  Cost train:  2322.2480690699977  Cost test:  2407.217539009995
Iteration :  38604  Cost train:  2322.2464233070227  Cost test:  2407.2158293229418
Iteration :  38605  Cost train:  2322.244777572636  Cost test:  2407.214119662861
Iteration :  38606  Cost train:  2322.2431318668373  Cost test:  2407.212410029751
Iteration :  38607  Cost train:  2322.241486189624  Cost test:  2407.210700423612
Iteration :  38608  Cost train:  2322.2398405409976  Cost test:  2407.2089908444427
Iteration :  38609  Cost train:  2322.238194920957  Cost test:  2407.2072812922443
Iteration :  38610  Cost train:  2322.236549329501  Cost test:  2407.2055717670146
Iteration :  38611  Cost train:  2322.234903766629  Cost test:  2407.203862268755
Iteration :  38612  Cost train:  2322.233258232341  Cost test:  2407.2021527974634
Iteration :  38613  Cost train:  2322.2316127266363  Cost test:  2407.2004433531406
Iteration :  38614  Cost train:  2322.2299672495133  Cost test:  2407.198733935785
Iteration :  38615  Cost train:  2322.2283218009725  Cost test:  2407.1970245453977
Iteration :  38616  Cost train:  2322.2266763810126  Cost test:  2407.1953151819766
Iteration :  38617  Cost train:  2322.2250309896335  Cost test:  2407.193605845523
Iteration :  38618  Cost train:  2322.2233856268335  Cost test:  2407.1918965360346
Iteration :  38619  Cost train:  2322.221740292613  Cost test:  2407.190187253513
Iteration :  38620  Cost train:  2322.220094986971  Cost test:  2407.1884779979564
Iteration :  38621  Cost train:  2322.218449709907  Cost test:  2407.1867687693643
Iteration :  38622  Cost train:  2322.21680446142  Cost test:  2407.1850595677374
Iteration :  38623  Cost train:  2322.2151592415103  Cost test:  2407.183350393074
Iteration :  38624  Cost train:  2322.213514050176  Cost test:  2407.181641245374
Iteration :  38625  Cost train:  2322.211868887417  Cost test:  2407.179932124638
Iteration :  38626  Cost train:  2322.210223753233  Cost test:  2407.1782230308645
Iteration :  38627  Cost train:  2322.208578647623  Cost test:  2407.176513964054
Iteration :  38628  Cost train:  2322.2069335705864  Cost test:  2407.174804924205
Iteration :  38629  Cost train:  2322.2052885221233  Cost test:  2407.173095911318
Iteration :  38630  Cost train:  2322.203643502231  Cost test:  2407.1713869253917
Iteration :  38631  Cost train:  2322.2019985109114  Cost test:  2407.169677966426
Iteration :  38632  Cost train:  2322.2003535481626  Cost test:  2407.1679690344204
Iteration :  38633  Cost train:  2322.198708613984  Cost test:  2407.1662601293756
Iteration :  38634  Cost train:  2322.1970637083746  Cost test:  2407.1645512512896
Iteration :  38635  Cost train:  2322.195418831335  Cost test:  2407.1628424001633
Iteration :  38636  Cost train:  2322.193773982863  Cost test:  2407.1611335759944
Iteration :  38637  Cost train:  2322.1921291629583  Cost test:  2407.159424778785
Iteration :  38638  Cost train:  2322.1904843716216  Cost test:  2407.157716008533
Iteration :  38639  Cost train:  2322.1888396088516  Cost test:  2407.1560072652383
Iteration :  38640  Cost train:  2322.1871948746466  Cost test:  2407.1542985489004
Iteration :  38641  Cost train:  2322.185550169008  Cost test:  2407.1525898595196
Iteration :  38642  Cost train:  2322.1839054919324  Cost test:  2407.150881197094
Iteration :  38643  Cost train:  2322.182260843422  Cost test:  2407.149172561625
Iteration :  38644  Cost train:  2322.1806162234743  Cost test:  2407.14746395311
Iteration :  38645  Cost train:  2322.178971632089  Cost test:  2407.1457553715513
Iteration :  38646  Cost train:  2322.177327069266  Cost test:  2407.1440468169467
Iteration :  38647  Cost train:  2322.175682535005  Cost test:  2407.142338289296
Iteration :  38648  Cost train:  2322.174038029304  Cost test:  2407.1406297885983
Iteration :  38649  Cost train:  2322.1723935521627  Cost test:  2407.138921314855
Iteration :  38650  Cost train:  2322.1707491035822  Cost test:  2407.137212868063
Iteration :  38651  Cost train:  2322.1691046835595  Cost test:  2407.1355044482248
Iteration :  38652  Cost train:  2322.1674602920953  Cost test:  2407.133796055337
Iteration :  38653  Cost train:  2322.1658159291887  Cost test:  2407.132087689402
Iteration :  38654  Cost train:  2322.164171594839  Cost test:  2407.130379350417
Iteration :  38655  Cost train:  2322.162527289046  Cost test:  2407.1286710383843
Iteration :  38656  Cost train:  2322.160883011808  Cost test:  2407.1269627533
Iteration :  38657  Cost train:  2322.159238763126  Cost test:  2407.1252544951662
Iteration :  38658  Cost train:  2322.1575945429972  Cost test:  2407.123546263982
Iteration :  38659  Cost train:  2322.1559503514227  Cost test:  2407.121838059747
Iteration :  38660  Cost train:  2322.1543061884017  Cost test:  2407.12012988246
Iteration :  38661  Cost train:  2322.1526620539325  Cost test:  2407.118421732121
Iteration :  38662  Cost train:  2322.1510179480156  Cost test:  2407.1167136087297
Iteration :  38663  Cost train:  2322.1493738706495  Cost test:  2407.1150055122866
Iteration :  38664  Cost train:  2322.1477298218347  Cost test:  2407.1132974427896
Iteration :  38665  Cost train:  2322.1460858015694  Cost test:  2407.111589400239
Iteration :  38666  Cost train:  2322.1444418098536  Cost test:  2407.1098813846343
Iteration :  38667  Cost train:  2322.1427978466863  Cost test:  2407.1081733959763
Iteration :  38668  Cost train:  2322.1411539120672  Cost test:  2407.1064654342626
Iteration :  38669  Cost train:  2322.139510005995  Cost test:  2407.104757499494
Iteration :  38670  Cost train:  2322.1378661284707  Cost test:  2407.10304959167
Iteration :  38671  Cost train:  2322.136222279492  Cost test:  2407.1013417107893
Iteration :  38672  Cost train:  2322.1345784590585  Cost test:  2407.099633856852
Iteration :  38673  Cost train:  2322.1329346671696  Cost test:  2407.097926029858
Iteration :  38674  Cost train:  2322.1312909038256  Cost test:  2407.096218229807
Iteration :  38675  Cost train:  2322.1296471690252  Cost test:  2407.094510456698
Iteration :  38676  Cost train:  2322.1280034627675  Cost test:  2407.0928027105306
Iteration :  38677  Cost train:  2322.1263597850525  Cost test:  2407.091094991305
Iteration :  38678  Cost train:  2322.1247161358788  Cost test:  2407.0893872990205
Iteration :  38679  Cost train:  2322.123072515246  Cost test:  2407.0876796336765
Iteration :  38680  Cost train:  2322.121428923154  Cost test:  2407.085971995272
Iteration :  38681  Cost train:  2322.119785359602  Cost test:  2407.084264383808
Iteration :  38682  Cost train:  2322.1181418245887  Cost test:  2407.082556799283
Iteration :  38683  Cost train:  2322.1164983181143  Cost test:  2407.0808492416973
Iteration :  38684  Cost train:  2322.1148548401775  Cost test:  2407.079141711049
Iteration :  38685  Cost train:  2322.1132113907775  Cost test:  2407.0774342073396
Iteration :  38686  Cost train:  2322.1115679699155  Cost test:  2407.0757267305676
Iteration :  38687  Cost train:  2322.1099245775886  Cost test:  2407.074019280733
Iteration :  38688  Cost train:  2322.108281213797  Cost test:  2407.072311857835
Iteration :  38689  Cost train:  2322.1066378785404  Cost test:  2407.0706044618737
Iteration :  38690  Cost train:  2322.1049945718178  Cost test:  2407.0688970928477
Iteration :  38691  Cost train:  2322.1033512936287  Cost test:  2407.0671897507573
Iteration :  38692  Cost train:  2322.1017080439724  Cost test:  2407.0654824356025
Iteration :  38693  Cost train:  2322.1000648228483  Cost test:  2407.0637751473823
Iteration :  38694  Cost train:  2322.098421630256  Cost test:  2407.062067886096
Iteration :  38695  Cost train:  2322.096778466194  Cost test:  2407.060360651744
Iteration :  38696  Cost train:  2322.0951353306627  Cost test:  2407.058653444325
Iteration :  38697  Cost train:  2322.0934922236606  Cost test:  2407.0569462638387
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Iteration :  38699  Cost train:  2322.090206095244  Cost test:  2407.0535319836645
Iteration :  38700  Cost train:  2322.0885630738276  Cost test:  2407.051824883975
Iteration :  38701  Cost train:  2322.086920080938  Cost test:  2407.0501178112168
Iteration :  38702  Cost train:  2322.0852771165746  Cost test:  2407.0484107653897
Iteration :  38703  Cost train:  2322.083634180738  Cost test:  2407.046703746493
Iteration :  38704  Cost train:  2322.0819912734255  Cost test:  2407.0449967545264
Iteration :  38705  Cost train:  2322.0803483946383  Cost test:  2407.0432897894893
Iteration :  38706  Cost train:  2322.078705544375  Cost test:  2407.041582851381
Iteration :  38707  Cost train:  2322.0770627226348  Cost test:  2407.0398759402024
Iteration :  38708  Cost train:  2322.0754199294174  Cost test:  2407.0381690559516
Iteration :  38709  Cost train:  2322.0737771647223  Cost test:  2407.0364621986287
Iteration :  38710  Cost train:  2322.072134428548  Cost test:  2407.0347553682336
Iteration :  38711  Cost train:  2322.070491720895  Cost test:  2407.0330485647655
Iteration :  38712  Cost train:  2322.0688490417624  Cost test:  2407.031341788224
Iteration :  38713  Cost train:  2322.0672063911484  Cost test:  2407.0296350386093
Iteration :  38714  Cost train:  2322.065563769054  Cost test:  2407.0279283159193
Iteration :  38715  Cost train:  2322.0639211754774  Cost test:  2407.026221620156
Iteration :  38716  Cost train:  2322.0622786104186  Cost test:  2407.0245149513166
Iteration :  38717  Cost train:  2322.0606360738766  Cost test:  2407.022808309403
Iteration :  38718  Cost train:  2322.058993565851  Cost test:  2407.0211016944127
Iteration :  38719  Cost train:  2322.057351086341  Cost test:  2407.019395106346
Iteration :  38720  Cost train:  2322.0557086353465  Cost test:  2407.017688545203
Iteration :  38721  Cost train:  2322.0540662128665  Cost test:  2407.015982010983
Iteration :  38722  Cost train:  2322.0524238189  Cost test:  2407.0142755036854
Iteration :  38723  Cost train:  2322.0507814534467  Cost test:  2407.01256902331
Iteration :  38724  Cost train:  2322.0491391165056  Cost test:  2407.0108625698554
Iteration :  38725  Cost train:  2322.047496808077  Cost test:  2407.009156143323
Iteration :  38726  Cost train:  2322.045854528159  Cost test:  2407.007449743711
Iteration :  38727  Cost train:  2322.044212276752  Cost test:  2407.0057433710194
Iteration :  38728  Cost train:  2322.042570053855  Cost test:  2407.0040370252473
Iteration :  38729  Cost train:  2322.0409278594675  Cost test:  2407.0023307063952
Iteration :  38730  Cost train:  2322.039285693589  Cost test:  2407.0006244144624
Iteration :  38731  Cost train:  2322.037643556218  Cost test:  2406.998918149448
Iteration :  38732  Cost train:  2322.036001447355  Cost test:  2406.997211911352
Iteration :  38733  Cost train:  2322.034359366998  Cost test:  2406.995505700174
Iteration :  38734  Cost train:  2322.0327173151477  Cost test:  2406.993799515913
Iteration :  38735  Cost train:  2322.0310752918035  Cost test:  2406.9920933585695
Iteration :  38736  Cost train:  2322.0294332969634  Cost test:  2406.990387228142
Iteration :  38737  Cost train:  2322.0277913306277  Cost test:  2406.9886811246315
Iteration :  38738  Cost train:  2322.026149392796  Cost test:  2406.9869750480357
Iteration :  38739  Cost train:  2322.024507483467  Cost test:  2406.985268998356
Iteration :  38740  Cost train:  2322.022865602641  Cost test:  2406.9835629755908
Iteration :  38741  Cost train:  2322.0212237503165  Cost test:  2406.9818569797403
Iteration :  38742  Cost train:  2322.0195819264927  Cost test:  2406.9801510108036
Iteration :  38743  Cost train:  2322.01794013117  Cost test:  2406.978445068781
Iteration :  38744  Cost train:  2322.0162983643463  Cost test:  2406.976739153671
Iteration :  38745  Cost train:  2322.0146566260228  Cost test:  2406.9750332654744
Iteration :  38746  Cost train:  2322.013014916198  Cost test:  2406.9733274041896
Iteration :  38747  Cost train:  2322.01137323487  Cost test:  2406.9716215698177
Iteration :  38748  Cost train:  2322.0097315820403  Cost test:  2406.9699157623563
Iteration :  38749  Cost train:  2322.008089957707  Cost test:  2406.968209981807
Iteration :  38750  Cost train:  2322.0064483618694  Cost test:  2406.9665042281677
Iteration :  38751  Cost train:  2322.004806794528  Cost test:  2406.9647985014385
Iteration :  38752  Cost train:  2322.003165255681  Cost test:  2406.963092801619
Iteration :  38753  Cost train:  2322.001523745328  Cost test:  2406.9613871287097
Iteration :  38754  Cost train:  2321.999882263469  Cost test:  2406.959681482709
Iteration :  38755  Cost train:  2321.9982408101023  Cost test:  2406.957975863617
Iteration :  38756  Cost train:  2321.9965993852284  Cost test:  2406.9562702714334
Iteration :  38757  Cost train:  2321.994957988846  Cost test:  2406.9545647061573
Iteration :  38758  Cost train:  2321.9933166209544  Cost test:  2406.952859167788
Iteration :  38759  Cost train:  2321.9916752815534  Cost test:  2406.9511536563264
Iteration :  38760  Cost train:  2321.990033970642  Cost test:  2406.9494481717707
Iteration :  38761  Cost train:  2321.98839268822  Cost test:  2406.9477427141214
Iteration :  38762  Cost train:  2321.986751434286  Cost test:  2406.946037283378
Iteration :  38763  Cost train:  2321.98511020884  Cost test:  2406.9443318795397
Iteration :  38764  Cost train:  2321.9834690118814  Cost test:  2406.942626502606
Iteration :  38765  Cost train:  2321.981827843409  Cost test:  2406.9409211525763
Iteration :  38766  Cost train:  2321.980186703423  Cost test:  2406.939215829451
Iteration :  38767  Cost train:  2321.9785455919223  Cost test:  2406.9375105332297
Iteration :  38768  Cost train:  2321.976904508906  Cost test:  2406.9358052639104
Iteration :  38769  Cost train:  2321.9752634543734  Cost test:  2406.9341000214945
Iteration :  38770  Cost train:  2321.9736224283247  Cost test:  2406.932394805981
Iteration :  38771  Cost train:  2321.9719814307587  Cost test:  2406.930689617369
Iteration :  38772  Cost train:  2321.970340461675  Cost test:  2406.9289844556583
Iteration :  38773  Cost train:  2321.9686995210727  Cost test:  2406.9272793208484
Iteration :  38774  Cost train:  2321.967058608951  Cost test:  2406.92557421294
Iteration :  38775  Cost train:  2321.9654177253096  Cost test:  2406.9238691319315
Iteration :  38776  Cost train:  2321.963776870148  Cost test:  2406.922164077822
Iteration :  38777  Cost train:  2321.9621360434653  Cost test:  2406.920459050613
Iteration :  38778  Cost train:  2321.9604952452614  Cost test:  2406.9187540503012
Iteration :  38779  Cost train:  2321.9588544755347  Cost test:  2406.9170490768893
Iteration :  38780  Cost train:  2321.9572137342852  Cost test:  2406.915344130375
Iteration :  38781  Cost train:  2321.955573021512  Cost test:  2406.913639210759
Iteration :  38782  Cost train:  2321.953932337215  Cost test:  2406.911934318039
Iteration :  38783  Cost train:  2321.9522916813926  Cost test:  2406.9102294522168
Iteration :  38784  Cost train:  2321.950651054045  Cost test:  2406.9085246132904
Iteration :  38785  Cost train:  2321.949010455172  Cost test:  2406.90681980126
Iteration :  38786  Cost train:  2321.9473698847714  Cost test:  2406.9051150161254
Iteration :  38787  Cost train:  2321.9457293428436  Cost test:  2406.9034102578858
Iteration :  38788  Cost train:  2321.944088829388  Cost test:  2406.901705526541
Iteration :  38789  Cost train:  2321.9424483444036  Cost test:  2406.9000008220905
Iteration :  38790  Cost train:  2321.9408078878905  Cost test:  2406.8982961445336
Iteration :  38791  Cost train:  2321.939167459847  Cost test:  2406.89659149387
Iteration :  38792  Cost train:  2321.9375270602736  Cost test:  2406.894886870099
Iteration :  38793  Cost train:  2321.935886689168  Cost test:  2406.8931822732216
Iteration :  38794  Cost train:  2321.9342463465314  Cost test:  2406.891477703236
Iteration :  38795  Cost train:  2321.932606032362  Cost test:  2406.889773160142
Iteration :  38796  Cost train:  2321.9309657466597  Cost test:  2406.8880686439397
Iteration :  38797  Cost train:  2321.929325489424  Cost test:  2406.8863641546277
Iteration :  38798  Cost train:  2321.927685260654  Cost test:  2406.8846596922067
Iteration :  38799  Cost train:  2321.9260450603488  Cost test:  2406.882955256676
Iteration :  38800  Cost train:  2321.9244048885084  Cost test:  2406.8812508480337
Iteration :  38801  Cost train:  2321.9227647451316  Cost test:  2406.879546466281
Iteration :  38802  Cost train:  2321.9211246302175  Cost test:  2406.8778421114175
Iteration :  38803  Cost train:  2321.919484543766  Cost test:  2406.8761377834426
Iteration :  38804  Cost train:  2321.917844485777  Cost test:  2406.874433482355
Iteration :  38805  Cost train:  2321.916204456249  Cost test:  2406.8727292081558
Iteration :  38806  Cost train:  2321.9145644551813  Cost test:  2406.8710249608425
Iteration :  38807  Cost train:  2321.9129244825745  Cost test:  2406.869320740417
Iteration :  38808  Cost train:  2321.911284538426  Cost test:  2406.8676165468773
Iteration :  38809  Cost train:  2321.9096446227372  Cost test:  2406.865912380223
Iteration :  38810  Cost train:  2321.908004735506  Cost test:  2406.8642082404544
Iteration :  38811  Cost train:  2321.906364876733  Cost test:  2406.862504127572
Iteration :  38812  Cost train:  2321.9047250464155  Cost test:  2406.8608000415725
Iteration :  38813  Cost train:  2321.903085244555  Cost test:  2406.859095982458
Iteration :  38814  Cost train:  2321.90144547115  Cost test:  2406.857391950227
Iteration :  38815  Cost train:  2321.8998057262  Cost test:  2406.855687944879
Iteration :  38816  Cost train:  2321.8981660097043  Cost test:  2406.853983966414
Iteration :  38817  Cost train:  2321.8965263216623  Cost test:  2406.8522800148316
Iteration :  38818  Cost train:  2321.8948866620735  Cost test:  2406.850576090131
Iteration :  38819  Cost train:  2321.893247030937  Cost test:  2406.848872192313
Iteration :  38820  Cost train:  2321.891607428252  Cost test:  2406.847168321375
Iteration :  38821  Cost train:  2321.8899678540183  Cost test:  2406.8454644773187
Iteration :  38822  Cost train:  2321.8883283082355  Cost test:  2406.8437606601424
Iteration :  38823  Cost train:  2321.8866887909026  Cost test:  2406.842056869846
Iteration :  38824  Cost train:  2321.8850493020186  Cost test:  2406.8403531064287
Iteration :  38825  Cost train:  2321.883409841583  Cost test:  2406.838649369891
Iteration :  38826  Cost train:  2321.8817704095964  Cost test:  2406.836945660232
Iteration :  38827  Cost train:  2321.8801310060567  Cost test:  2406.835241977451
Iteration :  38828  Cost train:  2321.8784916309633  Cost test:  2406.833538321548
Iteration :  38829  Cost train:  2321.876852284316  Cost test:  2406.8318346925225
Iteration :  38830  Cost train:  2321.8752129661143  Cost test:  2406.8301310903735
Iteration :  38831  Cost train:  2321.873573676358  Cost test:  2406.8284275151013
Iteration :  38832  Cost train:  2321.8719344150454  Cost test:  2406.8267239667052
Iteration :  38833  Cost train:  2321.8702951821765  Cost test:  2406.825020445185
Iteration :  38834  Cost train:  2321.8686559777507  Cost test:  2406.82331695054
Iteration :  38835  Cost train:  2321.867016801767  Cost test:  2406.8216134827703
Iteration :  38836  Cost train:  2321.865377654225  Cost test:  2406.819910041874
Iteration :  38837  Cost train:  2321.8637385351244  Cost test:  2406.8182066278528
Iteration :  38838  Cost train:  2321.8620994444636  Cost test:  2406.8165032407046
Iteration :  38839  Cost train:  2321.860460382243  Cost test:  2406.8147998804297
Iteration :  38840  Cost train:  2321.858821348462  Cost test:  2406.8130965470273
Iteration :  38841  Cost train:  2321.857182343119  Cost test:  2406.811393240498
Iteration :  38842  Cost train:  2321.8555433662136  Cost test:  2406.8096899608404
Iteration :  38843  Cost train:  2321.8539044177455  Cost test:  2406.807986708054
Iteration :  38844  Cost train:  2321.8522654977146  Cost test:  2406.8062834821385
Iteration :  38845  Cost train:  2321.8506266061195  Cost test:  2406.8045802830943
Iteration :  38846  Cost train:  2321.8489877429597  Cost test:  2406.8028771109193
Iteration :  38847  Cost train:  2321.8473489082344  Cost test:  2406.8011739656154
Iteration :  38848  Cost train:  2321.845710101944  Cost test:  2406.7994708471797
Iteration :  38849  Cost train:  2321.844071324086  Cost test:  2406.797767755614
Iteration :  38850  Cost train:  2321.842432574662  Cost test:  2406.7960646909164
Iteration :  38851  Cost train:  2321.8407938536693  Cost test:  2406.794361653087
Iteration :  38852  Cost train:  2321.8391551611085  Cost test:  2406.792658642125
Iteration :  38853  Cost train:  2321.837516496979  Cost test:  2406.7909556580307
Iteration :  38854  Cost train:  2321.835877861279  Cost test:  2406.789252700803
Iteration :  38855  Cost train:  2321.83423925401  Cost test:  2406.7875497704417
Iteration :  38856  Cost train:  2321.832600675169  Cost test:  2406.7858468669465
Iteration :  38857  Cost train:  2321.8309621247568  Cost test:  2406.7841439903173
Iteration :  38858  Cost train:  2321.829323602772  Cost test:  2406.7824411405527
Iteration :  38859  Cost train:  2321.8276851092146  Cost test:  2406.780738317653
Iteration :  38860  Cost train:  2321.826046644084  Cost test:  2406.7790355216175
Iteration :  38861  Cost train:  2321.8244082073793  Cost test:  2406.777332752446
Iteration :  38862  Cost train:  2321.8227697990997  Cost test:  2406.775630010138
Iteration :  38863  Cost train:  2321.8211314192445  Cost test:  2406.7739272946933
Iteration :  38864  Cost train:  2321.819493067814  Cost test:  2406.7722246061107
Iteration :  38865  Cost train:  2321.817854744806  Cost test:  2406.7705219443906
Iteration :  38866  Cost train:  2321.8162164502214  Cost test:  2406.7688193095323
Iteration :  38867  Cost train:  2321.8145781840585  Cost test:  2406.767116701536
Iteration :  38868  Cost train:  2321.8129399463173  Cost test:  2406.7654141204
Iteration :  38869  Cost train:  2321.8113017369974  Cost test:  2406.763711566124
Iteration :  38870  Cost train:  2321.809663556097  Cost test:  2406.762009038709
Iteration :  38871  Cost train:  2321.8080254036163  Cost test:  2406.7603065381536
Iteration :  38872  Cost train:  2321.806387279555  Cost test:  2406.758604064457
Iteration :  38873  Cost train:  2321.804749183912  Cost test:  2406.75690161762
Iteration :  38874  Cost train:  2321.8031111166865  Cost test:  2406.7551991976406
Iteration :  38875  Cost train:  2321.8014730778777  Cost test:  2406.7534968045197
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Iteration :  38877  Cost train:  2321.79819708551  Cost test:  2406.75009209885
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Iteration :  38880  Cost train:  2321.7932833100695  Cost test:  2406.7449852417694
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Iteration :  38882  Cost train:  2321.7900076018436  Cost test:  2406.7415808046608
Iteration :  38883  Cost train:  2321.7883697903494  Cost test:  2406.7398786263884
Iteration :  38884  Cost train:  2321.7867320072664  Cost test:  2406.73817647497
Iteration :  38885  Cost train:  2321.7850942525943  Cost test:  2406.7364743504054
Iteration :  38886  Cost train:  2321.783456526332  Cost test:  2406.7347722526947
Iteration :  38887  Cost train:  2321.781818828479  Cost test:  2406.733070181837
Iteration :  38888  Cost train:  2321.7801811590352  Cost test:  2406.731368137832
Iteration :  38889  Cost train:  2321.778543518  Cost test:  2406.729666120678
Iteration :  38890  Cost train:  2321.776905905372  Cost test:  2406.727964130376
Iteration :  38891  Cost train:  2321.7752683211506  Cost test:  2406.7262621669256
Iteration :  38892  Cost train:  2321.7736307653363  Cost test:  2406.724560230326
Iteration :  38893  Cost train:  2321.7719932379273  Cost test:  2406.7228583205765
Iteration :  38894  Cost train:  2321.7703557389236  Cost test:  2406.7211564376776
Iteration :  38895  Cost train:  2321.768718268324  Cost test:  2406.719454581628
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Iteration :  38904  Cost train:  2321.7539823110274  Cost test:  2406.70413908534
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Iteration :  38906  Cost train:  2321.750707966246  Cost test:  2406.70073593703
Iteration :  38907  Cost train:  2321.7490708364508  Cost test:  2406.6990344031424
Iteration :  38908  Cost train:  2321.7474337350527  Cost test:  2406.697332896098
Iteration :  38909  Cost train:  2321.7457966620495  Cost test:  2406.6956314158983
Iteration :  38910  Cost train:  2321.7441596174413  Cost test:  2406.6939299625406
Iteration :  38911  Cost train:  2321.7425226012283  Cost test:  2406.6922285360265
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Iteration :  38913  Cost train:  2321.739248653981  Cost test:  2406.688825763525
Iteration :  38914  Cost train:  2321.737611722947  Cost test:  2406.6871244175363
Iteration :  38915  Cost train:  2321.7359748203044  Cost test:  2406.685423098389
Iteration :  38916  Cost train:  2321.7343379460535  Cost test:  2406.6837218060823
Iteration :  38917  Cost train:  2321.7327011001926  Cost test:  2406.682020540616
Iteration :  38918  Cost train:  2321.731064282722  Cost test:  2406.6803193019896
Iteration :  38919  Cost train:  2321.729427493641  Cost test:  2406.6786180902027
Iteration :  38920  Cost train:  2321.7277907329485  Cost test:  2406.6769169052545
Iteration :  38921  Cost train:  2321.726154000644  Cost test:  2406.675215747145
Iteration :  38922  Cost train:  2321.724517296727  Cost test:  2406.6735146158735
Iteration :  38923  Cost train:  2321.722880621197  Cost test:  2406.67181351144
Iteration :  38924  Cost train:  2321.7212439740533  Cost test:  2406.6701124338438
Iteration :  38925  Cost train:  2321.719607355295  Cost test:  2406.6684113830843
Iteration :  38926  Cost train:  2321.717970764921  Cost test:  2406.6667103591612
Iteration :  38927  Cost train:  2321.716334202932  Cost test:  2406.665009362074
Iteration :  38928  Cost train:  2321.7146976693266  Cost test:  2406.6633083918227
Iteration :  38929  Cost train:  2321.713061164104  Cost test:  2406.661607448407
Iteration :  38930  Cost train:  2321.7114246872643  Cost test:  2406.6599065318255
Iteration :  38931  Cost train:  2321.709788238806  Cost test:  2406.6582056420784
Iteration :  38932  Cost train:  2321.7081518187288  Cost test:  2406.656504779165
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Iteration :  38934  Cost train:  2321.7048790637155  Cost test:  2406.6531031338395
Iteration :  38935  Cost train:  2321.703242728778  Cost test:  2406.6514023514255
Iteration :  38936  Cost train:  2321.7016064222194  Cost test:  2406.649701595844
Iteration :  38937  Cost train:  2321.6999701440386  Cost test:  2406.648000867094
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Iteration :  38939  Cost train:  2321.696697672809  Cost test:  2406.6445994900887
Iteration :  38940  Cost train:  2321.6950614797584  Cost test:  2406.6428988418315
Iteration :  38941  Cost train:  2321.6934253150835  Cost test:  2406.641198220405
Iteration :  38942  Cost train:  2321.6917891787825  Cost test:  2406.6394976258075
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Iteration :  38948  Cost train:  2321.681972956819  Cost test:  2406.6292946216254
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Iteration :  38950  Cost train:  2321.678701109801  Cost test:  2406.62589383485
Iteration :  38951  Cost train:  2321.6770652288465  Cost test:  2406.6241934817017
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Iteration :  38954  Cost train:  2321.672157756191  Cost test:  2406.6190925832066
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Iteration :  38960  Cost train:  2321.6623435767638  Cost test:  2406.608891510459
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Iteration :  38962  Cost train:  2321.659072410531  Cost test:  2406.6054913674543
Iteration :  38963  Cost train:  2321.657436869958  Cost test:  2406.603791336184
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Iteration :  38966  Cost train:  2321.6525304184006  Cost test:  2406.5986914032915
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Iteration :  38969  Cost train:  2321.6476242220765  Cost test:  2406.593591711772
Iteration :  38970  Cost train:  2321.645988880017  Cost test:  2406.591891868235
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Iteration :  39281  Cost train:  2321.1387701036006  Cost test:  2406.064539480951
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Iteration :  42004  Cost train:  2316.8120547607473  Cost test:  2401.5560464339937
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Iteration :  47610  Cost train:  2308.511516439751  Cost test:  2392.8598821734063
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Iteration :  47666  Cost train:  2308.432480724156  Cost test:  2392.7767981848665
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Iteration :  47688  Cost train:  2308.4014511410905  Cost test:  2392.744177826763
Iteration :  47689  Cost train:  2308.4000409755868  Cost test:  2392.7426953482036
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Iteration :  47724  Cost train:  2308.350699973123  Cost test:  2392.6908231102966
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Iteration :  47727  Cost train:  2308.3464720821294  Cost test:  2392.686378231121
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Iteration :  47729  Cost train:  2308.34365360545  Cost test:  2392.6834150934533
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Iteration :  48775  Cost train:  2306.882355590744  Cost test:  2391.1462314523246
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Iteration :  52748  Cost train:  2301.5561300001673  Cost test:  2385.5286390249653
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Iteration :  52850  Cost train:  2301.42389623581  Cost test:  2385.388878439701
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Iteration :  52859  Cost train:  2301.4122390785537  Cost test:  2385.3765570709133
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Iteration :  69288  Cost train:  2282.6802114469383  Cost test:  2365.432045044888
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Iteration :  69290  Cost train:  2282.6782082532163  Cost test:  2365.4298960787814
Iteration :  69291  Cost train:  2282.677206678937  Cost test:  2365.4288216185932
Iteration :  69292  Cost train:  2282.676205119712  Cost test:  2365.4277471736486
Iteration :  69293  Cost train:  2282.6752035755417  Cost test:  2365.426672743947
Iteration :  69294  Cost train:  2282.6742020464244  Cost test:  2365.4255983294884
Iteration :  69295  Cost train:  2282.6732005323615  Cost test:  2365.424523930271
Iteration :  69296  Cost train:  2282.6721990333513  Cost test:  2365.4234495462965
Iteration :  69297  Cost train:  2282.6711975493936  Cost test:  2365.422375177564
Iteration :  69298  Cost train:  2282.670196080489  Cost test:  2365.4213008240727
Iteration :  69299  Cost train:  2282.669194626636  Cost test:  2365.420226485822
Iteration :  69300  Cost train:  2282.668193187836  Cost test:  2365.4191521628127
Iteration :  69301  Cost train:  2282.6671917640865  Cost test:  2365.418077855044
Iteration :  69302  Cost train:  2282.666190355389  Cost test:  2365.4170035625157
Iteration :  69303  Cost train:  2282.6651889617424  Cost test:  2365.4159292852273
Iteration :  69304  Cost train:  2282.6641875831465  Cost test:  2365.4148550231785
Iteration :  69305  Cost train:  2282.663186219601  Cost test:  2365.4137807763695
Iteration :  69306  Cost train:  2282.6621848711065  Cost test:  2365.412706544799
Iteration :  69307  Cost train:  2282.661183537661  Cost test:  2365.411632328468
Iteration :  69308  Cost train:  2282.660182219265  Cost test:  2365.4105581273757
Iteration :  69309  Cost train:  2282.659180915919  Cost test:  2365.409483941521
Iteration :  69310  Cost train:  2282.6581796276214  Cost test:  2365.408409770905
Iteration :  69311  Cost train:  2282.6571783543727  Cost test:  2365.407335615526
Iteration :  69312  Cost train:  2282.656177096172  Cost test:  2365.406261475385
Iteration :  69313  Cost train:  2282.6551758530195  Cost test:  2365.405187350481
Iteration :  69314  Cost train:  2282.654174624915  Cost test:  2365.4041132408133
Iteration :  69315  Cost train:  2282.653173411857  Cost test:  2365.4030391463825
Iteration :  69316  Cost train:  2282.6521722138473  Cost test:  2365.401965067188
Iteration :  69317  Cost train:  2282.651171030884  Cost test:  2365.4008910032294
Iteration :  69318  Cost train:  2282.6501698629677  Cost test:  2365.3998169545066
Iteration :  69319  Cost train:  2282.649168710097  Cost test:  2365.3987429210188
Iteration :  69320  Cost train:  2282.6481675722725  Cost test:  2365.3976689027663
Iteration :  69321  Cost train:  2282.647166449494  Cost test:  2365.3965948997484
Iteration :  69322  Cost train:  2282.64616534176  Cost test:  2365.395520911966
Iteration :  69323  Cost train:  2282.6451642490715  Cost test:  2365.3944469394164
Iteration :  69324  Cost train:  2282.644163171428  Cost test:  2365.3933729821015
Iteration :  69325  Cost train:  2282.643162108829  Cost test:  2365.3922990400197
Iteration :  69326  Cost train:  2282.642161061274  Cost test:  2365.391225113172
Iteration :  69327  Cost train:  2282.6411600287624  Cost test:  2365.3901512015573
Iteration :  69328  Cost train:  2282.640159011295  Cost test:  2365.3890773051744
Iteration :  69329  Cost train:  2282.6391580088703  Cost test:  2365.3880034240246
Iteration :  69330  Cost train:  2282.638157021489  Cost test:  2365.3869295581067
Iteration :  69331  Cost train:  2282.6371560491502  Cost test:  2365.3858557074213
Iteration :  69332  Cost train:  2282.6361550918537  Cost test:  2365.384781871967
Iteration :  69333  Cost train:  2282.635154149599  Cost test:  2365.383708051744
Iteration :  69334  Cost train:  2282.6341532223864  Cost test:  2365.382634246752
Iteration :  69335  Cost train:  2282.633152310215  Cost test:  2365.381560456991
Iteration :  69336  Cost train:  2282.632151413085  Cost test:  2365.3804866824603
Iteration :  69337  Cost train:  2282.631150530996  Cost test:  2365.37941292316
Iteration :  69338  Cost train:  2282.6301496639476  Cost test:  2365.378339179089
Iteration :  69339  Cost train:  2282.6291488119386  Cost test:  2365.377265450248
Iteration :  69340  Cost train:  2282.62814797497  Cost test:  2365.3761917366364
Iteration :  69341  Cost train:  2282.6271471530413  Cost test:  2365.3751180382533
Iteration :  69342  Cost train:  2282.626146346152  Cost test:  2365.374044355099
Iteration :  69343  Cost train:  2282.6251455543015  Cost test:  2365.3729706871736
Iteration :  69344  Cost train:  2282.62414477749  Cost test:  2365.3718970344758
Iteration :  69345  Cost train:  2282.623144015716  Cost test:  2365.370823397006
Iteration :  69346  Cost train:  2282.6221432689813  Cost test:  2365.3697497747635
Iteration :  69347  Cost train:  2282.6211425372844  Cost test:  2365.368676167748
Iteration :  69348  Cost train:  2282.6201418206247  Cost test:  2365.36760257596
Iteration :  69349  Cost train:  2282.6191411190016  Cost test:  2365.3665289993987
Iteration :  69350  Cost train:  2282.6181404324166  Cost test:  2365.3654554380632
Iteration :  69351  Cost train:  2282.6171397608678  Cost test:  2365.3643818919545
Iteration :  69352  Cost train:  2282.616139104355  Cost test:  2365.363308361071
Iteration :  69353  Cost train:  2282.6151384628783  Cost test:  2365.3622348454132
Iteration :  69354  Cost train:  2282.6141378364377  Cost test:  2365.3611613449802
Iteration :  69355  Cost train:  2282.6131372250325  Cost test:  2365.360087859773
Iteration :  69356  Cost train:  2282.6121366286625  Cost test:  2365.3590143897895
Iteration :  69357  Cost train:  2282.611136047327  Cost test:  2365.3579409350314
Iteration :  69358  Cost train:  2282.610135481026  Cost test:  2365.3568674954968
Iteration :  69359  Cost train:  2282.60913492976  Cost test:  2365.3557940711853
Iteration :  69360  Cost train:  2282.608134393527  Cost test:  2365.354720662098
Iteration :  69361  Cost train:  2282.607133872328  Cost test:  2365.353647268234
Iteration :  69362  Cost train:  2282.606133366163  Cost test:  2365.352573889593
Iteration :  69363  Cost train:  2282.60513287503  Cost test:  2365.351500526174
Iteration :  69364  Cost train:  2282.6041323989302  Cost test:  2365.3504271779775
Iteration :  69365  Cost train:  2282.6031319378626  Cost test:  2365.3493538450025
Iteration :  69366  Cost train:  2282.602131491828  Cost test:  2365.3482805272497
Iteration :  69367  Cost train:  2282.601131060824  Cost test:  2365.3472072247187
Iteration :  69368  Cost train:  2282.6001306448525  Cost test:  2365.346133937408
Iteration :  69369  Cost train:  2282.599130243912  Cost test:  2365.3450606653187
Iteration :  69370  Cost train:  2282.5981298580023  Cost test:  2365.34398740845
Iteration :  69371  Cost train:  2282.5971294871233  Cost test:  2365.3429141668016
Iteration :  69372  Cost train:  2282.5961291312747  Cost test:  2365.3418409403735
Iteration :  69373  Cost train:  2282.595128790456  Cost test:  2365.3407677291643
Iteration :  69374  Cost train:  2282.594128464667  Cost test:  2365.339694533174
Iteration :  69375  Cost train:  2282.5931281539074  Cost test:  2365.338621352404
Iteration :  69376  Cost train:  2282.5921278581773  Cost test:  2365.337548186853
Iteration :  69377  Cost train:  2282.5911275774756  Cost test:  2365.3364750365195
Iteration :  69378  Cost train:  2282.590127311803  Cost test:  2365.3354019014046
Iteration :  69379  Cost train:  2282.5891270611583  Cost test:  2365.334328781508
Iteration :  69380  Cost train:  2282.5881268255416  Cost test:  2365.3332556768287
Iteration :  69381  Cost train:  2282.5871266049526  Cost test:  2365.3321825873672
Iteration :  69382  Cost train:  2282.586126399391  Cost test:  2365.331109513122
Iteration :  69383  Cost train:  2282.5851262088563  Cost test:  2365.330036454094
Iteration :  69384  Cost train:  2282.5841260333486  Cost test:  2365.328963410283
Iteration :  69385  Cost train:  2282.5831258728667  Cost test:  2365.3278903816877
Iteration :  69386  Cost train:  2282.582125727412  Cost test:  2365.326817368308
Iteration :  69387  Cost train:  2282.5811255969825  Cost test:  2365.325744370144
Iteration :  69388  Cost train:  2282.5801254815783  Cost test:  2365.3246713871963
Iteration :  69389  Cost train:  2282.5791253812  Cost test:  2365.323598419463
Iteration :  69390  Cost train:  2282.578125295846  Cost test:  2365.322525466944
Iteration :  69391  Cost train:  2282.5771252255167  Cost test:  2365.32145252964
Iteration :  69392  Cost train:  2282.576125170212  Cost test:  2365.3203796075504
Iteration :  69393  Cost train:  2282.5751251299316  Cost test:  2365.319306700674
Iteration :  69394  Cost train:  2282.5741251046747  Cost test:  2365.3182338090114
Iteration :  69395  Cost train:  2282.5731250944414  Cost test:  2365.317160932562
Iteration :  69396  Cost train:  2282.5721250992306  Cost test:  2365.316088071326
Convergence Achieved at  69396.0  iteration
Cost Minima Found :  2282.5721250992306
Betas : 
X0              100.502009
T1              200.340085
RH_1           1693.635762
T2              570.569947
RH_2           -126.459750
T3              651.656435
RH_3            913.109605
T4               48.016358
RH_4            566.464450
T5              -75.447710
RH_5             12.829196
RH_6            234.609591
T7             -173.332595
RH_7           -782.099893
T8              345.122979
RH_8          -1577.812382
RH_9           -743.747050
T_out           394.279614
Press_mm_hg      -5.917737
RH_out         -685.408989
Windspeed       496.478061
Tdewpoint       211.734332
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
Iteration :  109  Cost train:  4699.725151244447  Cost test:  4826.461334065434
Iteration :  110  Cost train:  4689.405032722035  Cost test:  4709.484461338859
Iteration :  111  Cost train:  4679.132531905506  Cost test:  4805.611038113325
Iteration :  112  Cost train:  4668.907428596511  Cost test:  4689.22026615031
Iteration :  113  Cost train:  4658.729503615403  Cost test:  4784.951528084699
Iteration :  114  Cost train:  4648.598538796419  Cost test:  4669.143727539292
Iteration :  115  Cost train:  4638.514316983173  Cost test:  4764.481049165222
Iteration :  116  Cost train:  4628.476622023865  Cost test:  4649.253109047221
Iteration :  117  Cost train:  4618.485238766649  Cost test:  4744.1978627137305
Iteration :  118  Cost train:  4608.539953055031  Cost test:  4629.54669026779
Iteration :  119  Cost train:  4598.640551723276  Cost test:  4724.100246112944
Iteration :  120  Cost train:  4588.786822591716  Cost test:  4610.022766698604
Iteration :  121  Cost train:  4578.978554462342  Cost test:  4704.186492621575
Iteration :  122  Cost train:  4569.215537114155  Cost test:  4590.679649594098
Iteration :  123  Cost train:  4559.497561298708  Cost test:  4684.454911227973
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Iteration :  2017  Cost train:  2439.4786588935062  Cost test:  2513.6426977337333
Iteration :  2018  Cost train:  2439.464203878176  Cost test:  2512.3436122604817
Iteration :  2019  Cost train:  2439.4497590048313  Cost test:  2513.614462331681
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Iteration :  6925  Cost train:  2399.6392946397377  Cost test:  2480.0870958897476
Iteration :  6926  Cost train:  2399.6342341169716  Cost test:  2480.082970295265
Iteration :  6927  Cost train:  2399.6291742985472  Cost test:  2480.0788746752146
Iteration :  6928  Cost train:  2399.6241151842614  Cost test:  2480.074750250037
Iteration :  6929  Cost train:  2399.619056773912  Cost test:  2480.070655662833
Iteration :  6930  Cost train:  2399.613999067296  Cost test:  2480.0665324059255
Iteration :  6931  Cost train:  2399.6089420642124  Cost test:  2480.062438851165
Iteration :  6932  Cost train:  2399.6038857644576  Cost test:  2480.0583167614977
Iteration :  6933  Cost train:  2399.5988301678312  Cost test:  2480.0542242387764
Iteration :  6934  Cost train:  2399.5937752741293  Cost test:  2480.050103315321
Iteration :  6935  Cost train:  2399.5887210831515  Cost test:  2480.0460118242336
Iteration :  6936  Cost train:  2399.583667594695  Cost test:  2480.0418920659617
Iteration :  6937  Cost train:  2399.578614808558  Cost test:  2480.0378016061027
Iteration :  6938  Cost train:  2399.573562724539  Cost test:  2480.0336830119895
Iteration :  6939  Cost train:  2399.5685113424356  Cost test:  2480.029593582952
Iteration :  6940  Cost train:  2399.563460662047  Cost test:  2480.025476151974
Iteration :  6941  Cost train:  2399.5584106831707  Cost test:  2480.0213877533497
Iteration :  6942  Cost train:  2399.5533614056067  Cost test:  2480.017271484486
Iteration :  6943  Cost train:  2399.5483128291517  Cost test:  2480.0131841158664
Iteration :  6944  Cost train:  2399.5432649536046  Cost test:  2480.0090690080974
Iteration :  6945  Cost train:  2399.538217778765  Cost test:  2480.0049826690724
Iteration :  6946  Cost train:  2399.5331713044307  Cost test:  2480.000868721381
Iteration :  6947  Cost train:  2399.528125530401  Cost test:  2479.9967834115396
Iteration :  6948  Cost train:  2399.5230804564744  Cost test:  2479.99267062291
Iteration :  6949  Cost train:  2399.51803608245  Cost test:  2479.9885863418403
Iteration :  6950  Cost train:  2399.512992408127  Cost test:  2479.984474711258
Iteration :  6951  Cost train:  2399.507949433304  Cost test:  2479.9803914585486
Iteration :  6952  Cost train:  2399.50290715778  Cost test:  2479.976280985002
Iteration :  6953  Cost train:  2399.4978655813547  Cost test:  2479.972198760239
Iteration :  6954  Cost train:  2399.492824703827  Cost test:  2479.9680894427174
Iteration :  6955  Cost train:  2399.4877845249953  Cost test:  2479.964008245486
Iteration :  6956  Cost train:  2399.4827450446605  Cost test:  2479.959900082983
Iteration :  6957  Cost train:  2399.4777062626213  Cost test:  2479.9558199128683
Iteration :  6958  Cost train:  2399.472668178677  Cost test:  2479.9517129043757
Iteration :  6959  Cost train:  2399.467630792627  Cost test:  2479.9476337609613
Iteration :  6960  Cost train:  2399.462594104271  Cost test:  2479.943527905476
Iteration :  6961  Cost train:  2399.457558113409  Cost test:  2479.9394497883454
Iteration :  6962  Cost train:  2399.4525228198404  Cost test:  2479.935345084863
Iteration :  6963  Cost train:  2399.4474882233653  Cost test:  2479.9312679935983
Iteration :  6964  Cost train:  2399.4424543237833  Cost test:  2479.927164441119
Iteration :  6965  Cost train:  2399.437421120894  Cost test:  2479.9230883753007
Iteration :  6966  Cost train:  2399.432388614498  Cost test:  2479.918985972826
Iteration :  6967  Cost train:  2399.4273568043945  Cost test:  2479.9149109320347
Iteration :  6968  Cost train:  2399.4223256903842  Cost test:  2479.9108096785667
Iteration :  6969  Cost train:  2399.4172952722674  Cost test:  2479.906735662382
Iteration :  6970  Cost train:  2399.4122655498436  Cost test:  2479.9026355569254
Iteration :  6971  Cost train:  2399.407236522914  Cost test:  2479.8985625649257
Iteration :  6972  Cost train:  2399.4022081912776  Cost test:  2479.894463606487
Iteration :  6973  Cost train:  2399.3971805547367  Cost test:  2479.89039163825
Iteration :  6974  Cost train:  2399.3921536130906  Cost test:  2479.886293825838
Iteration :  6975  Cost train:  2399.387127366139  Cost test:  2479.882222880941
Iteration :  6976  Cost train:  2399.3821018136837  Cost test:  2479.878126213565
Iteration :  6977  Cost train:  2399.377076955525  Cost test:  2479.8740562915837
Iteration :  6978  Cost train:  2399.3720527914643  Cost test:  2479.8699607682556
Iteration :  6979  Cost train:  2399.3670293213013  Cost test:  2479.8658918687656
Iteration :  6980  Cost train:  2399.3620065448376  Cost test:  2479.8617974884987
Iteration :  6981  Cost train:  2399.3569844618733  Cost test:  2479.857729611075
Iteration :  6982  Cost train:  2399.35196307221  Cost test:  2479.853636372885
Iteration :  6983  Cost train:  2399.3469423756487  Cost test:  2479.8495695170996
Iteration :  6984  Cost train:  2399.34192237199  Cost test:  2479.845477420004
Iteration :  6985  Cost train:  2399.336903061036  Cost test:  2479.8414115854307
Iteration :  6986  Cost train:  2399.331884442587  Cost test:  2479.8373206284477
Iteration :  6987  Cost train:  2399.3268665164446  Cost test:  2479.833255814659
Iteration :  6988  Cost train:  2399.3218492824103  Cost test:  2479.829165996809
Iteration :  6989  Cost train:  2399.316832740285  Cost test:  2479.8251022033755
Iteration :  6990  Cost train:  2399.311816889871  Cost test:  2479.8210135236814
Iteration :  6991  Cost train:  2399.3068017309683  Cost test:  2479.816950750174
Iteration :  6992  Cost train:  2399.3017872633804  Cost test:  2479.81286320766
Iteration :  6993  Cost train:  2399.296773486908  Cost test:  2479.808801453647
Iteration :  6994  Cost train:  2399.291760401353  Cost test:  2479.804715047339
Iteration :  6995  Cost train:  2399.2867480065165  Cost test:  2479.80065431239
Iteration :  6996  Cost train:  2399.2817363022004  Cost test:  2479.7965690413157
Iteration :  6997  Cost train:  2399.276725288208  Cost test:  2479.792509324999
Iteration :  6998  Cost train:  2399.27171496434  Cost test:  2479.788425188187
Iteration :  6999  Cost train:  2399.266705330399  Cost test:  2479.7843664900697
Iteration :  7000  Cost train:  2399.261696386186  Cost test:  2479.780283486551
Iteration :  7001  Cost train:  2399.2566881315047  Cost test:  2479.7762258062
Iteration :  7002  Cost train:  2399.2516805661567  Cost test:  2479.7721439350075
Iteration :  7003  Cost train:  2399.2466736899437  Cost test:  2479.768087271988
Iteration :  7004  Cost train:  2399.2416675026684  Cost test:  2479.7640065321566
Iteration :  7005  Cost train:  2399.236662004134  Cost test:  2479.7599508860335
Iteration :  7006  Cost train:  2399.2316571941415  Cost test:  2479.7558712766
Iteration :  7007  Cost train:  2399.226653072494  Cost test:  2479.751816646937
Iteration :  7008  Cost train:  2399.221649638994  Cost test:  2479.7477381669382
Iteration :  7009  Cost train:  2399.216646893445  Cost test:  2479.7436845532993
Iteration :  7010  Cost train:  2399.211644835649  Cost test:  2479.7396072017746
Iteration :  7011  Cost train:  2399.206643465409  Cost test:  2479.735554603723
Iteration :  7012  Cost train:  2399.201642782527  Cost test:  2479.7314783797133
Iteration :  7013  Cost train:  2399.196642786807  Cost test:  2479.727426796811
Convergence Achieved at  7013.0  iteration
Cost Minima Found :  2399.196642786807
Betas : 
X0              57.000456
T1              27.584394
RH_1           237.166292
T2              98.275763
RH_2           -33.963312
T3              61.828243
RH_3           143.449266
T4               4.528881
RH_4           108.376317
T5             -13.935006
RH_5            27.308313
RH_6            22.234124
T7             -22.215959
RH_7           -97.898093
T8              26.557332
RH_8          -218.250802
RH_9           -81.008073
T_out          137.828965
Press_mm_hg     75.821215
RH_out        -563.353843
Windspeed      112.010108
Tdewpoint       15.685805
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
Iteration :  109  Cost train:  4699.725151244447  Cost test:  4826.461334065434
Iteration :  110  Cost train:  4689.405032722035  Cost test:  4709.484461338859
Iteration :  111  Cost train:  4679.132531905506  Cost test:  4805.611038113325
Iteration :  112  Cost train:  4668.907428596511  Cost test:  4689.22026615031
Iteration :  113  Cost train:  4658.729503615403  Cost test:  4784.951528084699
Iteration :  114  Cost train:  4648.598538796419  Cost test:  4669.143727539292
Iteration :  115  Cost train:  4638.514316983173  Cost test:  4764.481049165222
Iteration :  116  Cost train:  4628.476622023865  Cost test:  4649.253109047221
Iteration :  117  Cost train:  4618.485238766649  Cost test:  4744.1978627137305
Iteration :  118  Cost train:  4608.539953055031  Cost test:  4629.54669026779
Iteration :  119  Cost train:  4598.640551723276  Cost test:  4724.100246112944
Iteration :  120  Cost train:  4588.786822591716  Cost test:  4610.022766698604
Iteration :  121  Cost train:  4578.978554462342  Cost test:  4704.186492621575
Iteration :  122  Cost train:  4569.215537114155  Cost test:  4590.679649594098
Iteration :  123  Cost train:  4559.497561298708  Cost test:  4684.454911227973
Iteration :  124  Cost train:  4549.824418735552  Cost test:  4571.515665820162
Iteration :  125  Cost train:  4540.195902107774  Cost test:  4664.903826504962
Iteration :  126  Cost train:  4530.611805057552  Cost test:  4552.529157709706
Iteration :  127  Cost train:  4521.071922181705  Cost test:  4645.531578465981
Iteration :  128  Cost train:  4511.576049027327  Cost test:  4533.718482919843
Iteration :  129  Cost train:  4502.123982087253  Cost test:  4626.336522422788
Iteration :  130  Cost train:  4492.715518795848  Cost test:  4515.082014290255
Iteration :  131  Cost train:  4483.350457524569  Cost test:  4607.317028844169
Iteration :  132  Cost train:  4474.028597577596  Cost test:  4496.618139702992
Iteration :  133  Cost train:  4464.749739187557  Cost test:  4588.471483216195
Iteration :  134  Cost train:  4455.5136835112735  Cost test:  4478.3252619432815
Iteration :  135  Cost train:  4446.320232625415  Cost test:  4569.798285903653
Iteration :  136  Cost train:  4437.1691895221975  Cost test:  4460.2017985620105
Iteration :  137  Cost train:  4428.060358105327  Cost test:  4551.2958520126285
Iteration :  138  Cost train:  4418.993543185645  Cost test:  4442.246181739165
Iteration :  139  Cost train:  4409.9685504769395  Cost test:  4532.962611254896
Iteration :  140  Cost train:  4400.985186591761  Cost test:  4424.456858148827
Iteration :  141  Cost train:  4392.043259037327  Cost test:  4514.797007812767
Iteration :  142  Cost train:  4383.14257621131  Cost test:  4406.832288825022
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Iteration :  2010  Cost train:  2439.5801308034006  Cost test:  2512.4329454949107
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Iteration :  2014  Cost train:  2439.5220851264485  Cost test:  2512.3882235685023
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Iteration :  2017  Cost train:  2439.4786588935062  Cost test:  2513.6426977337333
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Iteration :  2019  Cost train:  2439.4497590048313  Cost test:  2513.614462331681
Iteration :  2020  Cost train:  2439.4353242401953  Cost test:  2512.321347559431
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Iteration :  2970  Cost train:  2428.113196702882  Cost test:  2503.2799453004295
Iteration :  2971  Cost train:  2428.102815540426  Cost test:  2503.412535823047
Iteration :  2972  Cost train:  2428.0924367710786  Cost test:  2503.2629818953783
Iteration :  2973  Cost train:  2428.08206039372  Cost test:  2503.394923479459
Iteration :  2974  Cost train:  2428.071686407229  Cost test:  2503.246025744408
Iteration :  2975  Cost train:  2428.0613148104894  Cost test:  2503.3773214071553
Iteration :  2976  Cost train:  2428.0509456023856  Cost test:  2503.229076844794
Iteration :  2977  Cost train:  2428.040578781803  Cost test:  2503.35972958945
Iteration :  2978  Cost train:  2428.0302143476324  Cost test:  2503.2121351938144
Iteration :  2979  Cost train:  2428.019852298763  Cost test:  2503.3421480097277
Iteration :  2980  Cost train:  2428.009492634089  Cost test:  2503.1952007887553
Iteration :  2981  Cost train:  2427.999135352504  Cost test:  2503.324576651441
Iteration :  2982  Cost train:  2427.988780452906  Cost test:  2503.1782736269047
Iteration :  2983  Cost train:  2427.9784279341934  Cost test:  2503.3070154981115
Iteration :  2984  Cost train:  2427.9680777952667  Cost test:  2503.1613537055555
Iteration :  2985  Cost train:  2427.9577300350297  Cost test:  2503.289464533328
Iteration :  2986  Cost train:  2427.9473846523865  Cost test:  2503.1444410220056
Iteration :  2987  Cost train:  2427.937041646245  Cost test:  2503.2719237407473
Iteration :  2988  Cost train:  2427.9267010155127  Cost test:  2503.1275355735556
Iteration :  2989  Cost train:  2427.9163627591015  Cost test:  2503.2543931040927
Iteration :  2990  Cost train:  2427.906026875924  Cost test:  2503.1106373575117
Iteration :  2991  Cost train:  2427.895693364895  Cost test:  2503.236872607156
Iteration :  2992  Cost train:  2427.885362224931  Cost test:  2503.0937463711825
Iteration :  2993  Cost train:  2427.875033454951  Cost test:  2503.2193622337927
Iteration :  2994  Cost train:  2427.8647070538746  Cost test:  2503.0768626118806
Iteration :  2995  Cost train:  2427.854383020625  Cost test:  2503.2018619679257
Iteration :  2996  Cost train:  2427.8440613541266  Cost test:  2503.059986076923
Iteration :  2997  Cost train:  2427.8337420533057  Cost test:  2503.1843717935435
Iteration :  2998  Cost train:  2427.8234251170898  Cost test:  2503.0431167636293
Iteration :  2999  Cost train:  2427.81311054441  Cost test:  2503.1668916946987
Iteration :  3000  Cost train:  2427.802798334197  Cost test:  2503.026254669323
Iteration :  3001  Cost train:  2427.792488485386  Cost test:  2503.1494216555097
Iteration :  3002  Cost train:  2427.7821809969114  Cost test:  2503.00939979133
Iteration :  3003  Cost train:  2427.771875867712  Cost test:  2503.1319616601577
Iteration :  3004  Cost train:  2427.761573096726  Cost test:  2502.99255212698
Iteration :  3005  Cost train:  2427.7512726828954  Cost test:  2503.1145116928897
Iteration :  3006  Cost train:  2427.740974625163  Cost test:  2502.9757116736055
Iteration :  3007  Cost train:  2427.730678922473  Cost test:  2503.0970717380137
Iteration :  3008  Cost train:  2427.7203855737735  Cost test:  2502.9588784285424
Iteration :  3009  Cost train:  2427.7100945780116  Cost test:  2503.0796417799024
Iteration :  3010  Cost train:  2427.699805934139  Cost test:  2502.9420523891276
Iteration :  3011  Cost train:  2427.689519641107  Cost test:  2503.0622218029916
Iteration :  3012  Cost train:  2427.6792356978694  Cost test:  2502.925233552703
Iteration :  3013  Cost train:  2427.668954103382  Cost test:  2503.044811791778
Iteration :  3014  Cost train:  2427.658674856603  Cost test:  2502.908421916611
Iteration :  3015  Cost train:  2427.6483979564905  Cost test:  2503.0274117308218
Iteration :  3016  Cost train:  2427.638123402006  Cost test:  2502.8916174781984
Iteration :  3017  Cost train:  2427.6278511921128  Cost test:  2503.0100216047417
Iteration :  3018  Cost train:  2427.6175813257746  Cost test:  2502.874820234813
Iteration :  3019  Cost train:  2427.607313801958  Cost test:  2502.9926413982216
Iteration :  3020  Cost train:  2427.5970486196306  Cost test:  2502.8580301838047
Iteration :  3021  Cost train:  2427.5867857777625  Cost test:  2502.9752710960042
Iteration :  3022  Cost train:  2427.576525275326  Cost test:  2502.841247322526
Iteration :  3023  Cost train:  2427.566267111292  Cost test:  2502.9579106828915
Iteration :  3024  Cost train:  2427.556011284637  Cost test:  2502.8244716483323
Iteration :  3025  Cost train:  2427.545757794337  Cost test:  2502.9405601437466
Iteration :  3026  Cost train:  2427.535506639371  Cost test:  2502.807703158579
Iteration :  3027  Cost train:  2427.525257818718  Cost test:  2502.9232194634924
Iteration :  3028  Cost train:  2427.51501133136  Cost test:  2502.7909418506247
Iteration :  3029  Cost train:  2427.50476717628  Cost test:  2502.905888627112
Iteration :  3030  Cost train:  2427.494525352463  Cost test:  2502.774187721829
Iteration :  3031  Cost train:  2427.484285858896  Cost test:  2502.8885676196455
Iteration :  3032  Cost train:  2427.474048694567  Cost test:  2502.7574407695543
Iteration :  3033  Cost train:  2427.463813858466  Cost test:  2502.8712564261928
Iteration :  3034  Cost train:  2427.453581349584  Cost test:  2502.740700991164
Iteration :  3035  Cost train:  2427.443351166915  Cost test:  2502.853955031912
Iteration :  3036  Cost train:  2427.4331233094535  Cost test:  2502.7239683840216
Iteration :  3037  Cost train:  2427.422897776195  Cost test:  2502.836663422018
Iteration :  3038  Cost train:  2427.412674566139  Cost test:  2502.7072429454943
Iteration :  3039  Cost train:  2427.4024536782845  Cost test:  2502.8193815817845
Iteration :  3040  Cost train:  2427.392235111632  Cost test:  2502.6905246729484
Iteration :  3041  Cost train:  2427.3820188651857  Cost test:  2502.8021094965425
Iteration :  3042  Cost train:  2427.3718049379495  Cost test:  2502.6738135637534
Iteration :  3043  Cost train:  2427.3615933289284  Cost test:  2502.784847151678
Iteration :  3044  Cost train:  2427.351384037131  Cost test:  2502.657109615278
Iteration :  3045  Cost train:  2427.3411770615667  Cost test:  2502.7675945326364
Iteration :  3046  Cost train:  2427.3309724012456  Cost test:  2502.6404128248937
Iteration :  3047  Cost train:  2427.32077005518  Cost test:  2502.7503516249153
Iteration :  3048  Cost train:  2427.3105700223846  Cost test:  2502.6237231899713
Iteration :  3049  Cost train:  2427.300372301873  Cost test:  2502.733118414072
Iteration :  3050  Cost train:  2427.290176892663  Cost test:  2502.6070407078832
Iteration :  3051  Cost train:  2427.2799837937737  Cost test:  2502.7158948857177
Iteration :  3052  Cost train:  2427.269793004224  Cost test:  2502.5903653760033
Iteration :  3053  Cost train:  2427.2596045230366  Cost test:  2502.698681025517
Iteration :  3054  Cost train:  2427.249418349233  Cost test:  2502.573697191705
Iteration :  3055  Cost train:  2427.2392344818386  Cost test:  2502.681476819193
Iteration :  3056  Cost train:  2427.22905291988  Cost test:  2502.5570361523623
Iteration :  3057  Cost train:  2427.2188736623834  Cost test:  2502.6642822525196
Iteration :  3058  Cost train:  2427.2086967083783  Cost test:  2502.540382255351
Iteration :  3059  Cost train:  2427.1985220568954  Cost test:  2502.647097311328
Iteration :  3060  Cost train:  2427.188349706966  Cost test:  2502.523735498047
Iteration :  3061  Cost train:  2427.178179657625  Cost test:  2502.6299219815
Iteration :  3062  Cost train:  2427.168011907906  Cost test:  2502.507095877824
Iteration :  3063  Cost train:  2427.157846456845  Cost test:  2502.6127562489737
Iteration :  3064  Cost train:  2427.1476833034812  Cost test:  2502.4904633920605
Iteration :  3065  Cost train:  2427.1375224468525  Cost test:  2502.595600099739
Iteration :  3066  Cost train:  2427.1273638860007  Cost test:  2502.473838038132
Iteration :  3067  Cost train:  2427.117207619967  Cost test:  2502.5784535198386
Iteration :  3068  Cost train:  2427.107053647796  Cost test:  2502.457219813414
Iteration :  3069  Cost train:  2427.096901968532  Cost test:  2502.561316495369
Iteration :  3070  Cost train:  2427.086752581222  Cost test:  2502.4406087152856
Iteration :  3071  Cost train:  2427.0766054849128  Cost test:  2502.5441890124766
Iteration :  3072  Cost train:  2427.0664606786545  Cost test:  2502.4240047411213
Iteration :  3073  Cost train:  2427.056318161498  Cost test:  2502.5270710573627
Iteration :  3074  Cost train:  2427.0461779324946  Cost test:  2502.407407888298
Iteration :  3075  Cost train:  2427.036039990698  Cost test:  2502.5099626162773
Iteration :  3076  Cost train:  2427.0259043351634  Cost test:  2502.390818154193
Iteration :  3077  Cost train:  2427.015770964947  Cost test:  2502.4928636755235
Iteration :  3078  Cost train:  2427.0056398791057  Cost test:  2502.3742355361824
Iteration :  3079  Cost train:  2426.9955110766996  Cost test:  2502.475774221456
Iteration :  3080  Cost train:  2426.985384556788  Cost test:  2502.357660031641
Iteration :  3081  Cost train:  2426.975260318433  Cost test:  2502.4586942404776
Iteration :  3082  Cost train:  2426.965138360698  Cost test:  2502.341091637946
Iteration :  3083  Cost train:  2426.9550186826477  Cost test:  2502.4416237190435
Iteration :  3084  Cost train:  2426.9449012833466  Cost test:  2502.3245303524727
Iteration :  3085  Cost train:  2426.9347861618626  Cost test:  2502.424562643659
Iteration :  3086  Cost train:  2426.9246733172645  Cost test:  2502.3079761725958
Iteration :  3087  Cost train:  2426.9145627486214  Cost test:  2502.4075110008785
Iteration :  3088  Cost train:  2426.9044544550047  Cost test:  2502.291429095689
Iteration :  3089  Cost train:  2426.8943484354872  Cost test:  2502.390468777306
Iteration :  3090  Cost train:  2426.8842446891417  Cost test:  2502.274889119127
Iteration :  3091  Cost train:  2426.874143215044  Cost test:  2502.373435959595
Iteration :  3092  Cost train:  2426.8640440122713  Cost test:  2502.258356240283
Iteration :  3093  Cost train:  2426.853947079899  Cost test:  2502.356412534448
Iteration :  3094  Cost train:  2426.8438524170083  Cost test:  2502.2418304565285
Iteration :  3095  Cost train:  2426.833760022678  Cost test:  2502.339398488616
Iteration :  3096  Cost train:  2426.82366989599  Cost test:  2502.2253117652367
Iteration :  3097  Cost train:  2426.8135820360276  Cost test:  2502.3223938088986
Iteration :  3098  Cost train:  2426.8034964418744  Cost test:  2502.208800163777
Iteration :  3099  Cost train:  2426.7934131126162  Cost test:  2502.3053984821427
Iteration :  3100  Cost train:  2426.783332047339  Cost test:  2502.1922956495214
Iteration :  3101  Cost train:  2426.7732532451314  Cost test:  2502.2884124952434
Iteration :  3102  Cost train:  2426.7631767050825  Cost test:  2502.1757982198383
Iteration :  3103  Cost train:  2426.7531024262817  Cost test:  2502.271435835144
Iteration :  3104  Cost train:  2426.743030407822  Cost test:  2502.1593078720957
Iteration :  3105  Cost train:  2426.732960648795  Cost test:  2502.2544684888344
Iteration :  3106  Cost train:  2426.722893148296  Cost test:  2502.1428246036608
Iteration :  3107  Cost train:  2426.7128279054205  Cost test:  2502.2375104433513
Iteration :  3108  Cost train:  2426.7027649192637  Cost test:  2502.126348411901
Iteration :  3109  Cost train:  2426.692704188924  Cost test:  2502.220561685778
Iteration :  3110  Cost train:  2426.6826457135007  Cost test:  2502.10987929418
Iteration :  3111  Cost train:  2426.6725894920946  Cost test:  2502.2036222032452
Iteration :  3112  Cost train:  2426.662535523806  Cost test:  2502.093417247863
Iteration :  3113  Cost train:  2426.652483807739  Cost test:  2502.186691982929
Iteration :  3114  Cost train:  2426.6424343429953  Cost test:  2502.076962270311
Iteration :  3115  Cost train:  2426.6323871286822  Cost test:  2502.169771012051
Iteration :  3116  Cost train:  2426.6223421639047  Cost test:  2502.0605143588873
Iteration :  3117  Cost train:  2426.612299447771  Cost test:  2502.1528592778795
Iteration :  3118  Cost train:  2426.602258979389  Cost test:  2502.044073510951
Iteration :  3119  Cost train:  2426.5922207578687  Cost test:  2502.135956767727
Iteration :  3120  Cost train:  2426.5821847823213  Cost test:  2502.0276397238613
Iteration :  3121  Cost train:  2426.572151051859  Cost test:  2502.119063468952
Iteration :  3122  Cost train:  2426.5621195655945  Cost test:  2502.011212994975
Iteration :  3123  Cost train:  2426.5520903226434  Cost test:  2502.1021793689574
Iteration :  3124  Cost train:  2426.5420633221197  Cost test:  2501.9947933216486
Iteration :  3125  Cost train:  2426.5320385631426  Cost test:  2502.0853044551905
Iteration :  3126  Cost train:  2426.522016044828  Cost test:  2501.978380701237
Iteration :  3127  Cost train:  2426.511995766295  Cost test:  2502.068438715143
Iteration :  3128  Cost train:  2426.501977726665  Cost test:  2501.961975131092
Iteration :  3129  Cost train:  2426.4919619250586  Cost test:  2502.051582136352
Iteration :  3130  Cost train:  2426.4819483605984  Cost test:  2501.945576608565
Iteration :  3131  Cost train:  2426.4719370324083  Cost test:  2502.0347347063953
Iteration :  3132  Cost train:  2426.4619279396125  Cost test:  2501.9291851310068
Iteration :  3133  Cost train:  2426.451921081337  Cost test:  2502.0178964128977
Iteration :  3134  Cost train:  2426.441916456709  Cost test:  2501.912800695764
Iteration :  3135  Cost train:  2426.4319140648568  Cost test:  2502.0010672435246
Iteration :  3136  Cost train:  2426.421913904909  Cost test:  2501.8964233001843
Iteration :  3137  Cost train:  2426.411915975996  Cost test:  2501.9842471859865
Convergence Achieved at  3137.0  iteration
Cost Minima Found :  2426.411915975996
Betas : 
X0              50.915400
T1              14.514373
RH_1           107.184012
T2              51.290024
RH_2           -26.769808
T3              28.283545
RH_3            66.023806
T4               4.202032
RH_4            48.741698
T5              -5.829256
RH_5            12.517115
RH_6           -63.599637
T7              -8.030460
RH_7           -50.004085
T8              12.209429
RH_8          -107.811812
RH_9           -39.245345
T_out           80.359908
Press_mm_hg     73.482860
RH_out        -355.935002
Windspeed       58.198461
Tdewpoint        3.312146
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
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Iteration :  1254  Cost train:  2461.1926619480637  Cost test:  2529.6686569526796
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Iteration :  1256  Cost train:  2461.058590495906  Cost test:  2529.554723110466
Iteration :  1257  Cost train:  2460.9919157602258  Cost test:  2536.9947050795927
Iteration :  1258  Cost train:  2460.925480228579  Cost test:  2529.441675619447
Iteration :  1259  Cost train:  2460.8592828150836  Cost test:  2536.8474380495777
Iteration :  1260  Cost train:  2460.793322438863  Cost test:  2529.3295061178787
Iteration :  1261  Cost train:  2460.7275980240242  Cost test:  2536.701205029946
Iteration :  1262  Cost train:  2460.662108499633  Cost test:  2529.218206322501
Iteration :  1263  Cost train:  2460.596852799693  Cost test:  2536.555997036794
Iteration :  1264  Cost train:  2460.53182986312  Cost test:  2529.107768027803
Iteration :  1265  Cost train:  2460.467038633722  Cost test:  2536.411805167019
Iteration :  1266  Cost train:  2460.402478060177  Cost test:  2528.9981831053037
Iteration :  1267  Cost train:  2460.3381470960067  Cost test:  2536.268620597578
Iteration :  1268  Cost train:  2460.2740446995585  Cost test:  2528.88944350283
Iteration :  1269  Cost train:  2460.2101698339807  Cost test:  2536.1264345847635
Iteration :  1270  Cost train:  2460.1465214672016  Cost test:  2528.7815412438113
Iteration :  1271  Cost train:  2460.083098571905  Cost test:  2535.985238463479
Iteration :  1272  Cost train:  2460.019900125512  Cost test:  2528.6744684265723
Iteration :  1273  Cost train:  2459.9569251101566  Cost test:  2535.8450236465233
Iteration :  1274  Cost train:  2459.894172512664  Cost test:  2528.568217223636
Iteration :  1275  Cost train:  2459.83164132453  Cost test:  2535.7057816238776
Iteration :  1276  Cost train:  2459.7693305418984  Cost test:  2528.462779881035
Iteration :  1277  Cost train:  2459.7072391655397  Cost test:  2535.5675039620073
Iteration :  1278  Cost train:  2459.6453662008316  Cost test:  2528.3581487176248
Iteration :  1279  Cost train:  2459.5837106577346  Cost test:  2535.4301823031656
Iteration :  1280  Cost train:  2459.5222715507734  Cost test:  2528.2543161244066
Iteration :  1281  Cost train:  2459.4610478990135  Cost test:  2535.293808364697
Iteration :  1282  Cost train:  2459.4000387260426  Cost test:  2528.1512745638547
Iteration :  1283  Cost train:  2459.3392430599492  Cost test:  2535.1583739383605
Iteration :  1284  Cost train:  2459.2786599333003  Cost test:  2528.0490165692513
Iteration :  1285  Cost train:  2459.2182883831215  Cost test:  2535.023870889649
Iteration :  1286  Cost train:  2459.1581274508767  Cost test:  2527.947534744029
Iteration :  1287  Cost train:  2459.0981761824496  Cost test:  2534.8902911571176
Iteration :  1288  Cost train:  2459.038433628118  Cost test:  2527.846821761113
Iteration :  1289  Cost train:  2458.978898842539  Cost test:  2534.7576267517197
Iteration :  1290  Cost train:  2458.919570884726  Cost test:  2527.746870362279
Iteration :  1291  Cost train:  2458.8604488180276  Cost test:  2534.625869756146
Iteration :  1292  Cost train:  2458.801531710112  Cost test:  2527.647673357508
Iteration :  1293  Cost train:  2458.742818632941  Cost test:  2534.495012324175
Iteration :  1294  Cost train:  2458.6843086627564  Cost test:  2527.5492236243526
Iteration :  1295  Cost train:  2458.626000880054  Cost test:  2534.3650466800214
Iteration :  1296  Cost train:  2458.5678943695693  Cost test:  2527.451514107308
Iteration :  1297  Cost train:  2458.509988220255  Cost test:  2534.235965117696
Iteration :  1298  Cost train:  2458.4522815252617  Cost test:  2527.3545378171875
Iteration :  1299  Cost train:  2458.39477338192  Cost test:  2534.107760000377
Iteration :  1300  Cost train:  2458.3374628917204  Cost test:  2527.2582878305043
Iteration :  1301  Cost train:  2458.2803491602926  Cost test:  2533.9804237597677
Iteration :  1302  Cost train:  2458.223431297389  Cost test:  2527.162757288861
Iteration :  1303  Cost train:  2458.166708416864  Cost test:  2533.853948895486
Iteration :  1304  Cost train:  2458.110179636655  Cost test:  2527.0679393983423
Iteration :  1305  Cost train:  2458.053844078765  Cost test:  2533.7283279744383
Iteration :  1306  Cost train:  2457.9977008692413  Cost test:  2526.9738274289134
Iteration :  1307  Cost train:  2457.941749138161  Cost test:  2533.6035536302106
Iteration :  1308  Cost train:  2457.885988019606  Cost test:  2526.880414713826
Iteration :  1309  Cost train:  2457.8304166516523  Cost test:  2533.4796185624577
Iteration :  1310  Cost train:  2457.7750341763444  Cost test:  2526.7876946490287
Iteration :  1311  Cost train:  2457.7198397396814  Cost test:  2533.35651553631
Iteration :  1312  Cost train:  2457.6648324915977  Cost test:  2526.6956606925814
Iteration :  1313  Cost train:  2457.610011585944  Cost test:  2533.2342373817687
Iteration :  1314  Cost train:  2457.5553761804695  Cost test:  2526.604306364078
Iteration :  1315  Cost train:  2457.500925436805  Cost test:  2533.1127769931227
Iteration :  1316  Cost train:  2457.4466585204445  Cost test:  2526.513625244072
Iteration :  1317  Cost train:  2457.3925746007253  Cost test:  2532.992127328359
Iteration :  1318  Cost train:  2457.338672850813  Cost test:  2526.4236109735084
Iteration :  1319  Cost train:  2457.2849524476837  Cost test:  2532.8722814085872
Iteration :  1320  Cost train:  2457.2314125721045  Cost test:  2526.3342572531606
Iteration :  1321  Cost train:  2457.1780524086157  Cost test:  2532.7532323174614
Iteration :  1322  Cost train:  2457.124871145518  Cost test:  2526.2455578430754
Iteration :  1323  Cost train:  2457.071867974849  Cost test:  2532.634973200616
Iteration :  1324  Cost train:  2457.0190420923695  Cost test:  2526.1575065620164
Iteration :  1325  Cost train:  2456.9663926975463  Cost test:  2532.517497265098
Iteration :  1326  Cost train:  2456.9139189935336  Cost test:  2526.0700972869195
Iteration :  1327  Cost train:  2456.861620187157  Cost test:  2532.4007977788106
Iteration :  1328  Cost train:  2456.809495488896  Cost test:  2525.983323952348
Iteration :  1329  Cost train:  2456.757544112869  Cost test:  2532.2848680699585
Iteration :  1330  Cost train:  2456.7057652768117  Cost test:  2525.8971805499614
Iteration :  1331  Cost train:  2456.6541582020673  Cost test:  2532.1697015265017
Iteration :  1332  Cost train:  2456.6027221135637  Cost test:  2525.8116611279734
Iteration :  1333  Cost train:  2456.5514562398  Cost test:  2532.0552915956105
Iteration :  1334  Cost train:  2456.50035981283  Cost test:  2525.7267597906343
Iteration :  1335  Cost train:  2456.449432068244  Cost test:  2531.9416317831274
Iteration :  1336  Cost train:  2456.398672245155  Cost test:  2525.6424706977027
Iteration :  1337  Cost train:  2456.3480795861806  Cost test:  2531.828715653035
Iteration :  1338  Cost train:  2456.2976533374276  Cost test:  2525.558788063929
Iteration :  1339  Cost train:  2456.247392748475  Cost test:  2531.7165368269248
Iteration :  1340  Cost train:  2456.1972970723587  Cost test:  2525.475706158544
Iteration :  1341  Cost train:  2456.147365565556  Cost test:  2531.6050889834783
Convergence Achieved at  1341.0  iteration
Cost Minima Found :  2456.147365565556
Betas : 
X0              48.852865
T1               9.316613
RH_1            44.917449
T2              26.834747
RH_2           -16.812825
T3              15.304959
RH_3            26.308827
T4               5.775664
RH_4            18.180568
T5               0.378632
RH_5             1.902975
RH_6          -107.397611
T7               0.747324
RH_7           -26.298731
T8               8.503484
RH_8           -53.180884
RH_9           -20.052951
T_out           45.740793
Press_mm_hg     69.224407
RH_out        -199.643189
Windspeed       26.701669
Tdewpoint        1.977729
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
Iteration :  109  Cost train:  4699.725151244447  Cost test:  4826.461334065434
Iteration :  110  Cost train:  4689.405032722035  Cost test:  4709.484461338859
Iteration :  111  Cost train:  4679.132531905506  Cost test:  4805.611038113325
Iteration :  112  Cost train:  4668.907428596511  Cost test:  4689.22026615031
Iteration :  113  Cost train:  4658.729503615403  Cost test:  4784.951528084699
Iteration :  114  Cost train:  4648.598538796419  Cost test:  4669.143727539292
Iteration :  115  Cost train:  4638.514316983173  Cost test:  4764.481049165222
Iteration :  116  Cost train:  4628.476622023865  Cost test:  4649.253109047221
Iteration :  117  Cost train:  4618.485238766649  Cost test:  4744.1978627137305
Iteration :  118  Cost train:  4608.539953055031  Cost test:  4629.54669026779
Iteration :  119  Cost train:  4598.640551723276  Cost test:  4724.100246112944
Iteration :  120  Cost train:  4588.786822591716  Cost test:  4610.022766698604
Iteration :  121  Cost train:  4578.978554462342  Cost test:  4704.186492621575
Iteration :  122  Cost train:  4569.215537114155  Cost test:  4590.679649594098
Iteration :  123  Cost train:  4559.497561298708  Cost test:  4684.454911227973
Iteration :  124  Cost train:  4549.824418735552  Cost test:  4571.515665820162
Iteration :  125  Cost train:  4540.195902107774  Cost test:  4664.903826504962
Iteration :  126  Cost train:  4530.611805057552  Cost test:  4552.529157709706
Iteration :  127  Cost train:  4521.071922181705  Cost test:  4645.531578465981
Iteration :  128  Cost train:  4511.576049027327  Cost test:  4533.718482919843
Iteration :  129  Cost train:  4502.123982087253  Cost test:  4626.336522422788
Iteration :  130  Cost train:  4492.715518795848  Cost test:  4515.082014290255
Iteration :  131  Cost train:  4483.350457524569  Cost test:  4607.317028844169
Iteration :  132  Cost train:  4474.028597577596  Cost test:  4496.618139702992
Iteration :  133  Cost train:  4464.749739187557  Cost test:  4588.471483216195
Iteration :  134  Cost train:  4455.5136835112735  Cost test:  4478.3252619432815
Iteration :  135  Cost train:  4446.320232625415  Cost test:  4569.798285903653
Iteration :  136  Cost train:  4437.1691895221975  Cost test:  4460.2017985620105
Iteration :  137  Cost train:  4428.060358105327  Cost test:  4551.2958520126285
Iteration :  138  Cost train:  4418.993543185645  Cost test:  4442.246181739165
Iteration :  139  Cost train:  4409.9685504769395  Cost test:  4532.962611254896
Iteration :  140  Cost train:  4400.985186591761  Cost test:  4424.456858148827
Iteration :  141  Cost train:  4392.043259037327  Cost test:  4514.797007812767
Iteration :  142  Cost train:  4383.14257621131  Cost test:  4406.832288825022
Iteration :  143  Cost train:  4374.282947397772  Cost test:  4496.797500205778
Iteration :  144  Cost train:  4365.464182762994  Cost test:  4389.370949029123
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Iteration :  1101  Cost train:  2475.118206362278  Cost test:  2552.562809634403
Iteration :  1102  Cost train:  2474.9974851318816  Cost test:  2541.695163473812
Iteration :  1103  Cost train:  2474.8772496801935  Cost test:  2552.2991367670047
Iteration :  1104  Cost train:  2474.7574977839463  Cost test:  2541.4821466571993
Iteration :  1105  Cost train:  2474.6382272301335  Cost test:  2552.0375212414833
Iteration :  1106  Cost train:  2474.519435815958  Cost test:  2541.2709487913853
Iteration :  1107  Cost train:  2474.4011213487897  Cost test:  2551.7779448279553
Iteration :  1108  Cost train:  2474.283281646118  Cost test:  2541.0615527872565
Iteration :  1109  Cost train:  2474.1659145355006  Cost test:  2551.520389461764
Iteration :  1110  Cost train:  2474.0490178545224  Cost test:  2540.853941715296
Iteration :  1111  Cost train:  2473.9325894507465  Cost test:  2551.264837241972
Iteration :  1112  Cost train:  2473.8166271816667  Cost test:  2540.648098804105
Iteration :  1113  Cost train:  2473.701128914666  Cost test:  2551.0112704298626
Iteration :  1114  Cost train:  2473.5860925269662  Cost test:  2540.4440074389336
Iteration :  1115  Cost train:  2473.471515905585  Cost test:  2550.7596714474557
Iteration :  1116  Cost train:  2473.3573969472905  Cost test:  2540.241651160224
Iteration :  1117  Cost train:  2473.243733558556  Cost test:  2550.5100228760375
Iteration :  1118  Cost train:  2473.130523655514  Cost test:  2540.041013662174
Iteration :  1119  Cost train:  2473.017765163915  Cost test:  2550.2623074547046
Iteration :  1120  Cost train:  2472.905456019078  Cost test:  2539.8420787913064
Iteration :  1121  Cost train:  2472.7935941658507  Cost test:  2550.016508078922
Iteration :  1122  Cost train:  2472.682177558563  Cost test:  2539.6448305450526
Iteration :  1123  Cost train:  2472.571204160985  Cost test:  2549.772607799092
Iteration :  1124  Cost train:  2472.46067194628  Cost test:  2539.4492530703565
Iteration :  1125  Cost train:  2472.3505788969665  Cost test:  2549.530589819138
Iteration :  1126  Cost train:  2472.240923004869  Cost test:  2539.2553306622794
Iteration :  1127  Cost train:  2472.131702271081  Cost test:  2549.2904374951013
Iteration :  1128  Cost train:  2472.0229147059167  Cost test:  2539.0630477626314
Iteration :  1129  Cost train:  2471.9145583288723  Cost test:  2549.0521343337505
Iteration :  1130  Cost train:  2471.80663116858  Cost test:  2538.872388958604
Iteration :  1131  Cost train:  2471.6991312627706  Cost test:  2548.8156639912013
Iteration :  1132  Cost train:  2471.5920566582267  Cost test:  2538.6833389814183
Iteration :  1133  Cost train:  2471.4854054107445  Cost test:  2548.5810102715545
Iteration :  1134  Cost train:  2471.3791755850893  Cost test:  2538.495882704994
Iteration :  1135  Cost train:  2471.2733652549564  Cost test:  2548.34815712554
Iteration :  1136  Cost train:  2471.167972502928  Cost test:  2538.3100051446177
Iteration :  1137  Cost train:  2471.0629954204323  Cost test:  2548.1170886491805
Iteration :  1138  Cost train:  2470.958432107706  Cost test:  2538.125691455631
Iteration :  1139  Cost train:  2470.8542806737482  Cost test:  2547.887789082459
Iteration :  1140  Cost train:  2470.750539236284  Cost test:  2537.942926932134
Iteration :  1141  Cost train:  2470.6472059217226  Cost test:  2547.6602428080073
Iteration :  1142  Cost train:  2470.5442788651167  Cost test:  2537.76169700569
Iteration :  1143  Cost train:  2470.441756210124  Cost test:  2547.434434349798
Iteration :  1144  Cost train:  2470.339636108966  Cost test:  2537.5819872440534
Iteration :  1145  Cost train:  2470.23791672239  Cost test:  2547.210348371855
Iteration :  1146  Cost train:  2470.136596219629  Cost test:  2537.403783349901
Iteration :  1147  Cost train:  2470.035672778361  Cost test:  2546.9879696769763
Iteration :  1148  Cost train:  2469.9351445846733  Cost test:  2537.2270711595825
Iteration :  1149  Cost train:  2469.8350098330193  Cost test:  2546.7672832054586
Iteration :  1150  Cost train:  2469.7352667261844  Cost test:  2537.051836641875
Convergence Achieved at  1150.0  iteration
Cost Minima Found :  2469.7352667261844
Betas : 
X0              43.501272
T1               8.535825
RH_1            38.109179
T2              23.808360
RH_2           -15.437874
T3              13.747103
RH_3            21.882538
T4               5.703430
RH_4            14.805776
T5               0.886396
RH_5             0.590222
RH_6          -108.396891
T7               1.449003
RH_7           -23.628764
T8               7.938091
RH_8           -47.094227
RH_9           -18.037909
T_out           41.211330
Press_mm_hg     63.043373
RH_out        -179.020181
Windspeed       23.029588
Tdewpoint        1.962248
dtype: float64
Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
Iteration :  109  Cost train:  4699.725151244447  Cost test:  4826.461334065434
Iteration :  110  Cost train:  4689.405032722035  Cost test:  4709.484461338859
Iteration :  111  Cost train:  4679.132531905506  Cost test:  4805.611038113325
Iteration :  112  Cost train:  4668.907428596511  Cost test:  4689.22026615031
Iteration :  113  Cost train:  4658.729503615403  Cost test:  4784.951528084699
Iteration :  114  Cost train:  4648.598538796419  Cost test:  4669.143727539292
Iteration :  115  Cost train:  4638.514316983173  Cost test:  4764.481049165222
Iteration :  116  Cost train:  4628.476622023865  Cost test:  4649.253109047221
Iteration :  117  Cost train:  4618.485238766649  Cost test:  4744.1978627137305
Iteration :  118  Cost train:  4608.539953055031  Cost test:  4629.54669026779
Iteration :  119  Cost train:  4598.640551723276  Cost test:  4724.100246112944
Iteration :  120  Cost train:  4588.786822591716  Cost test:  4610.022766698604
Iteration :  121  Cost train:  4578.978554462342  Cost test:  4704.186492621575
Iteration :  122  Cost train:  4569.215537114155  Cost test:  4590.679649594098
Iteration :  123  Cost train:  4559.497561298708  Cost test:  4684.454911227973
Iteration :  124  Cost train:  4549.824418735552  Cost test:  4571.515665820162
Iteration :  125  Cost train:  4540.195902107774  Cost test:  4664.903826504962
Iteration :  126  Cost train:  4530.611805057552  Cost test:  4552.529157709706
Iteration :  127  Cost train:  4521.071922181705  Cost test:  4645.531578465981
Iteration :  128  Cost train:  4511.576049027327  Cost test:  4533.718482919843
Iteration :  129  Cost train:  4502.123982087253  Cost test:  4626.336522422788
Iteration :  130  Cost train:  4492.715518795848  Cost test:  4515.082014290255
Iteration :  131  Cost train:  4483.350457524569  Cost test:  4607.317028844169
Iteration :  132  Cost train:  4474.028597577596  Cost test:  4496.618139702992
Iteration :  133  Cost train:  4464.749739187557  Cost test:  4588.471483216195
Iteration :  134  Cost train:  4455.5136835112735  Cost test:  4478.3252619432815
Iteration :  135  Cost train:  4446.320232625415  Cost test:  4569.798285903653
Iteration :  136  Cost train:  4437.1691895221975  Cost test:  4460.2017985620105
Iteration :  137  Cost train:  4428.060358105327  Cost test:  4551.2958520126285
Iteration :  138  Cost train:  4418.993543185645  Cost test:  4442.246181739165
Iteration :  139  Cost train:  4409.9685504769395  Cost test:  4532.962611254896
Iteration :  140  Cost train:  4400.985186591761  Cost test:  4424.456858148827
Iteration :  141  Cost train:  4392.043259037327  Cost test:  4514.797007812767
Iteration :  142  Cost train:  4383.14257621131  Cost test:  4406.832288825022
Iteration :  143  Cost train:  4374.282947397772  Cost test:  4496.797500205778
Iteration :  144  Cost train:  4365.464182762994  Cost test:  4389.370949029123
Iteration :  145  Cost train:  4356.686093351576  Cost test:  4478.962561158386
Iteration :  146  Cost train:  4347.948491082074  Cost test:  4372.071328118565
Iteration :  147  Cost train:  4339.251188743211  Cost test:  4461.290677469036
Iteration :  148  Cost train:  4330.593999989701  Cost test:  4354.9319294162615
Iteration :  149  Cost train:  4321.976739338369  Cost test:  4443.7803498800995
Iteration :  150  Cost train:  4313.39922216397  Cost test:  4337.951270081756
Iteration :  151  Cost train:  4304.861264695496  Cost test:  4426.430092949308
Iteration :  152  Cost train:  4296.362684011985  Cost test:  4321.127880983369
Iteration :  153  Cost train:  4287.9032980386655  Cost test:  4409.238434922531
Iteration :  154  Cost train:  4279.482925543058  Cost test:  4304.4603065714955
Iteration :  155  Cost train:  4271.101386131102  Cost test:  4392.203917607198
Iteration :  156  Cost train:  4262.758500243201  Cost test:  4287.947104753167
Iteration :  157  Cost train:  4254.45408915037  Cost test:  4375.325096247385
Iteration :  158  Cost train:  4246.187974950504  Cost test:  4271.58684676754
Iteration :  159  Cost train:  4237.959980564389  Cost test:  4358.600539399739
Iteration :  160  Cost train:  4229.76992973207  Cost test:  4255.378117062906
Iteration :  161  Cost train:  4221.617647008818  Cost test:  4342.028828810755
Iteration :  162  Cost train:  4213.502957761666  Cost test:  4239.31951317443
Iteration :  163  Cost train:  4205.425688165381  Cost test:  4325.608559295011
Iteration :  164  Cost train:  4197.385665198889  Cost test:  4223.409645603407
Iteration :  165  Cost train:  4189.382716641492  Cost test:  4309.338338614689
Iteration :  166  Cost train:  4181.41667106918  Cost test:  4207.647137697362
Iteration :  167  Cost train:  4173.487357850935  Cost test:  4293.216787360164
Iteration :  168  Cost train:  4165.594607145094  Cost test:  4192.030625531408
Iteration :  169  Cost train:  4157.7382498956  Cost test:  4277.242538831643
Iteration :  170  Cost train:  4149.918117828452  Cost test:  4176.558757790474
Iteration :  171  Cost train:  4142.134043448153  Cost test:  4261.414238921733
Iteration :  172  Cost train:  4134.385860033964  Cost test:  4161.230195653035
Iteration :  173  Cost train:  4126.673401636381  Cost test:  4245.730545999699
Iteration :  174  Cost train:  4118.996503073542  Cost test:  4146.043612675481
Iteration :  175  Cost train:  4111.354999927696  Cost test:  4230.19013079586
Iteration :  176  Cost train:  4103.7487285417355  Cost test:  4130.997694677668
Iteration :  177  Cost train:  4096.177526015566  Cost test:  4214.79167628794
Iteration :  178  Cost train:  4088.6412302026342  Cost test:  4116.091139629881
Iteration :  179  Cost train:  4081.139679706506  Cost test:  4199.533877587954
Iteration :  180  Cost train:  4073.6727138772994  Cost test:  4101.322657540359
Iteration :  181  Cost train:  4066.2401728082496  Cost test:  4184.415441830289
Iteration :  182  Cost train:  4058.841897332368  Cost test:  4086.6909703439896
Iteration :  183  Cost train:  4051.477729018931  Cost test:  4169.435088060791
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Iteration :  665  Cost train:  2629.986030044413  Cost test:  2716.624046719897
Iteration :  666  Cost train:  2629.1833242835614  Cost test:  2686.322111085334
Iteration :  667  Cost train:  2628.3842452172807  Cost test:  2714.953240439154
Iteration :  668  Cost train:  2627.588776111621  Cost test:  2684.794783298365
Iteration :  669  Cost train:  2626.7969003099765  Cost test:  2713.2972095012105
Iteration :  670  Cost train:  2626.008601232721  Cost test:  2683.281535881438
Iteration :  671  Cost train:  2625.223862376863  Cost test:  2711.6558194258096
Iteration :  672  Cost train:  2624.442667315685  Cost test:  2681.782237859709
Iteration :  673  Cost train:  2623.664999698394  Cost test:  2710.0289369657708
Iteration :  674  Cost train:  2622.8908432497583  Cost test:  2680.2967594724996
Iteration :  675  Cost train:  2622.1201817697793  Cost test:  2708.4164300956313
Iteration :  676  Cost train:  2621.352999133326  Cost test:  2678.824972162048
Iteration :  677  Cost train:  2620.5892792897935  Cost test:  2706.8181680004136
Iteration :  678  Cost train:  2619.8290062627634  Cost test:  2677.3667485623823
Iteration :  679  Cost train:  2619.0721641496566  Cost test:  2705.234021064484
Iteration :  680  Cost train:  2618.3187371213903  Cost test:  2675.921962488306
Iteration :  681  Cost train:  2617.56870942204  Cost test:  2703.6638608605185
Iteration :  682  Cost train:  2616.8220653685044  Cost test:  2674.4904889244594
Iteration :  683  Cost train:  2616.078789350161  Cost test:  2702.107560138574
Iteration :  684  Cost train:  2615.33886582854  Cost test:  2673.0722040145056
Iteration :  685  Cost train:  2614.602279336989  Cost test:  2700.564992815259
Iteration :  686  Cost train:  2613.869014480326  Cost test:  2671.6669850504154
Iteration :  687  Cost train:  2613.1390559345327  Cost test:  2699.0360339629897
Iteration :  688  Cost train:  2612.41238844641  Cost test:  2670.2747104618247
Iteration :  689  Cost train:  2611.6889968332525  Cost test:  2697.5205597993745
Iteration :  690  Cost train:  2610.9688659825265  Cost test:  2668.89525980552
Iteration :  691  Cost train:  2610.251980851546  Cost test:  2696.0184476766663
Iteration :  692  Cost train:  2609.5383264671377  Cost test:  2667.5285137550177
Iteration :  693  Cost train:  2608.8278879253367  Cost test:  2694.5295760713248
Iteration :  694  Cost train:  2608.12065039106  Cost test:  2666.174354090212
Iteration :  695  Cost train:  2607.416599097782  Cost test:  2693.0538245736884
Iteration :  696  Cost train:  2606.7157193472226  Cost test:  2664.832663687159
Iteration :  697  Cost train:  2606.0179965090315  Cost test:  2691.5910738777047
Iteration :  698  Cost train:  2605.323416020472  Cost test:  2663.5033265079137
Iteration :  699  Cost train:  2604.631963386118  Cost test:  2690.1412057707958
Iteration :  700  Cost train:  2603.9436241775275  Cost test:  2662.18622759051
Iteration :  701  Cost train:  2603.258384032941  Cost test:  2688.704103123803
Iteration :  702  Cost train:  2602.576228656977  Cost test:  2660.881253038983
Iteration :  703  Cost train:  2601.8971438203125  Cost test:  2687.279649881014
Iteration :  704  Cost train:  2601.2211153593903  Cost test:  2659.5882900135075
Iteration :  705  Cost train:  2600.5481291761116  Cost test:  2685.8677310502767
Iteration :  706  Cost train:  2599.878171237532  Cost test:  2658.307226720643
Iteration :  707  Cost train:  2599.211227575554  Cost test:  2684.4682326932475
Iteration :  708  Cost train:  2598.5472842866384  Cost test:  2657.0379524036293
Iteration :  709  Cost train:  2597.8863275315025  Cost test:  2683.081041915668
Iteration :  710  Cost train:  2597.2283435348113  Cost test:  2655.780357332815
Iteration :  711  Cost train:  2596.573318584902  Cost test:  2681.7060468577733
Iteration :  712  Cost train:  2595.9212390334774  Cost test:  2654.5343327961373
Iteration :  713  Cost train:  2595.272091295309  Cost test:  2680.343136684789
Iteration :  714  Cost train:  2594.625861847954  Cost test:  2653.2997710897153
Iteration :  715  Cost train:  2593.982537231467  Cost test:  2678.992201577483
Iteration :  716  Cost train:  2593.342104048098  Cost test:  2652.0765655085256
Iteration :  717  Cost train:  2592.7045489620186  Cost test:  2677.6531327228436
Iteration :  718  Cost train:  2592.0698586990256  Cost test:  2650.8646103371493
Iteration :  719  Cost train:  2591.438020046266  Cost test:  2676.3258223048133
Iteration :  720  Cost train:  2590.8090198519394  Cost test:  2649.6638008406217
Iteration :  721  Cost train:  2590.1828450250287  Cost test:  2675.0101634951197
Iteration :  722  Cost train:  2589.559482535017  Cost test:  2648.4740332553497
Iteration :  723  Cost train:  2588.938919411604  Cost test:  2673.706050444204
Iteration :  724  Cost train:  2588.3211427444244  Cost test:  2647.2952047801473
Iteration :  725  Cost train:  2587.7061396827776  Cost test:  2672.413378272207
Iteration :  726  Cost train:  2587.093897435351  Cost test:  2646.1272135673025
Iteration :  727  Cost train:  2586.484403269943  Cost test:  2671.1320430600563
Iteration :  728  Cost train:  2585.877644513189  Cost test:  2644.969958713772
Iteration :  729  Cost train:  2585.2736085502906  Cost test:  2669.8619418406315
Iteration :  730  Cost train:  2584.6722828247457  Cost test:  2643.823340252431
Iteration :  731  Cost train:  2584.073654838082  Cost test:  2668.602972590007
Iteration :  732  Cost train:  2583.4777121495777  Cost test:  2642.6872591434203
Iteration :  733  Cost train:  2582.884442376007  Cost test:  2667.3550342187846
Iteration :  734  Cost train:  2582.2938331913665  Cost test:  2641.561617265556
Iteration :  735  Cost train:  2581.7058723266136  Cost test:  2666.118026563492
Iteration :  736  Cost train:  2581.120547569405  Cost test:  2640.4463174078373
Iteration :  737  Cost train:  2580.5378467638284  Cost test:  2664.8918503780783
Iteration :  738  Cost train:  2579.957757810145  Cost test:  2639.341263261017
Iteration :  739  Cost train:  2579.380268664534  Cost test:  2663.6764073254653
Iteration :  740  Cost train:  2578.8053673388267  Cost test:  2638.2463594092615
Iteration :  741  Cost train:  2578.2330419002533  Cost test:  2662.4715999691994
Iteration :  742  Cost train:  2577.6632804711894  Cost test:  2637.1615113218795
Iteration :  743  Cost train:  2577.096071228892  Cost test:  2661.2773317651713
Iteration :  744  Cost train:  2576.531402405254  Cost test:  2636.0866253451327
Iteration :  745  Cost train:  2575.9692622865505  Cost test:  2660.093507053401
Iteration :  746  Cost train:  2575.409639213183  Cost test:  2635.0216086941186
Iteration :  747  Cost train:  2574.8525215794352  Cost test:  2658.9200310499177
Iteration :  748  Cost train:  2574.297897833217  Cost test:  2633.966369444733
Iteration :  749  Cost train:  2573.7457564758215  Cost test:  2657.7568098387023
Iteration :  750  Cost train:  2573.1960860616787  Cost test:  2632.9208165256973
Iteration :  751  Cost train:  2572.648875198106  Cost test:  2656.6037503637062
Iteration :  752  Cost train:  2572.104112545066  Cost test:  2631.884859710675
Iteration :  753  Cost train:  2571.5617868149243  Cost test:  2655.4607604209486
Iteration :  754  Cost train:  2571.0218867722037  Cost test:  2630.858409610447
Iteration :  755  Cost train:  2570.484401233346  Cost test:  2654.3277486506827
Iteration :  756  Cost train:  2569.9493190664675  Cost test:  2629.8413776651614
Iteration :  757  Cost train:  2569.416629191129  Cost test:  2653.2046245296197
Iteration :  758  Cost train:  2568.8863205780895  Cost test:  2628.83367613666
Iteration :  759  Cost train:  2568.3583822490714  Cost test:  2652.091298363262
Iteration :  760  Cost train:  2567.832803276527  Cost test:  2627.8352181008754
Iteration :  761  Cost train:  2567.309572783407  Cost test:  2650.9876812782663
Iteration :  762  Cost train:  2566.7886799429166  Cost test:  2626.8459174403006
Iteration :  763  Cost train:  2566.270113978291  Cost test:  2649.8936852149054
Iteration :  764  Cost train:  2565.7538641625656  Cost test:  2625.8656888365113
Iteration :  765  Cost train:  2565.239919818337  Cost test:  2648.809222919583
Iteration :  766  Cost train:  2564.728270317545  Cost test:  2624.8944477627806
Iteration :  767  Cost train:  2564.218905081234  Cost test:  2647.7342079374184
Iteration :  768  Cost train:  2563.7118135793385  Cost test:  2623.9321104767478
Iteration :  769  Cost train:  2563.206985330441  Cost test:  2646.668554604919
Iteration :  770  Cost train:  2562.70440990156  Cost test:  2622.978594013162
Iteration :  771  Cost train:  2562.2040769079217  Cost test:  2645.6121780426893
Iteration :  772  Cost train:  2561.705976012736  Cost test:  2622.0338161766863
Convergence Achieved at  772.0  iteration
Cost Minima Found :  2561.705976012736
Betas : 
X0              38.295519
T1               6.894078
RH_1            25.164670
T2              17.531849
RH_2           -11.746804
T3              10.557750
RH_3            13.751759
T4               5.362185
RH_4             8.828612
T5               1.792590
RH_5            -1.103305
RH_6          -101.425995
T7               2.610794
RH_7           -17.459230
T8               6.701799
RH_8           -33.863331
RH_9           -13.265847
T_out           31.165655
Press_mm_hg     54.898733
RH_out        -132.599529
Windspeed       15.636231
Tdewpoint        1.901004
dtype: float64

bar_1=pd.concat([best_criteria.groupby('Convergence_criteria')['Cost_test'].min(),
           best_criteria.groupby('Convergence_criteria')['Iteration'].max()],axis=1)
bar_1['Convergence_criteria']=bar_1.index
bar_1

fig=go.Figure()
for i in x:
    fig.add_trace(go.Scatter(x=best_criteria.loc[best_criteria['Convergence_criteria']==i,'Cost_test'],
                            y=best_criteria.loc[best_criteria['Convergence_criteria']==i,'Iteration'],
                            name=i,
                             mode='lines'))
fig.update_layout(title='Cost Vs Iteration')
fig.update_yaxes(range=[0,2700])
#fig.update_xaxes(range=[0.001,0.5])
fig.show()u

fig=go.Figure()
fig.add_trace(go.Scatter(x=bar_1['Iteration'],
                        y=bar_1['Cost_test'],
                        mode='markers+lines+text',
                        text=bar_1['Convergence_criteria'],
                        textposition='top center',
                        line=dict(color='rgb(244,109,67)'),
                        marker=dict(
                        color=bar_1['Convergence_criteria'],
                        colorscale='Earth',
                        showscale=True,
                        size=12)))
fig.update_yaxes(range=[2300,2700])
fig.update_layout(title='Cost Vs Iteration',xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

CC=[0.001,0.005,0.01,0.05,0.1,0.5]
l=[]
for i in CC : l.append("Convergence "+str(i))
fig = go.Figure()
fig.add_trace(go.Bar(x=l,
                     y=bar_1['Cost_test'],
                    text=l,
                    textposition='outside'))
fig.update_yaxes(range=[2300,2700])
fig.update_layout(title='Cost Vs Convergence',xaxis=dict(title='Convergence criteria'),yaxis=dict(title='Cost'))
fig.show()

initial_params,params,graph_optimum=batch_gradient_descent_v3('lr',x_train,y_train,x_test,y_test,1,0.01,1000000)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  6131.881685171096  Cost test:  6137.643063447518
Iteration :  3  Cost train:  6114.950036447358  Cost test:  6257.204648270228
Iteration :  4  Cost train:  6098.096582375364  Cost test:  6104.156318193907
Iteration :  5  Cost train:  6081.320961290886  Cost test:  6223.246126446692
Iteration :  6  Cost train:  6064.622813202932  Cost test:  6070.97955231276
Iteration :  7  Cost train:  6048.0017797863575  Cost test:  6189.599018458445
Iteration :  8  Cost train:  6031.457504373746  Cost test:  6038.109898693779
Iteration :  9  Cost train:  6014.9896319479485  Cost test:  6156.260457438258
Iteration :  10  Cost train:  5998.597809134429  Cost test:  6005.544516725766
Iteration :  11  Cost train:  5982.281684193641  Cost test:  6123.227602953465
Iteration :  12  Cost train:  5966.040907013291  Cost test:  5973.280592051743
Iteration :  13  Cost train:  5949.875129101235  Cost test:  6090.4976407618515
Iteration :  14  Cost train:  5933.784003577571  Cost test:  5941.315336326316
Iteration :  15  Cost train:  5917.767185167294  Cost test:  6058.067782570457
Iteration :  16  Cost train:  5901.824330192935  Cost test:  5909.645986975292
Iteration :  17  Cost train:  5885.955096567227  Cost test:  6025.935265795524
Iteration :  18  Cost train:  5870.159143785517  Cost test:  5878.269806957827
Iteration :  19  Cost train:  5854.436132918621  Cost test:  5994.097353325712
Iteration :  20  Cost train:  5838.785726605505  Cost test:  5847.184084530155
Iteration :  21  Cost train:  5823.207589046092  Cost test:  5962.551333286796
Iteration :  22  Cost train:  5807.701385993831  Cost test:  5816.386133012359
Iteration :  23  Cost train:  5792.266784748646  Cost test:  5931.294518808916
Iteration :  24  Cost train:  5776.903454149845  Cost test:  5785.873290556194
Iteration :  25  Cost train:  5761.611064568772  Cost test:  5900.324247795519
Iteration :  26  Cost train:  5746.389287902081  Cost test:  5755.642919915949
Iteration :  27  Cost train:  5731.237797564271  Cost test:  5869.63788269508
Iteration :  28  Cost train:  5716.156268480953  Cost test:  5725.692408221266
Iteration :  29  Cost train:  5701.144377081776  Cost test:  5839.232810274476
Iteration :  30  Cost train:  5686.201801293329  Cost test:  5696.019166751826
Iteration :  31  Cost train:  5671.328220532456  Cost test:  5809.106441394566
Iteration :  32  Cost train:  5656.523315699188  Cost test:  5666.620630714123
Iteration :  33  Cost train:  5641.786769169868  Cost test:  5779.256210787915
Iteration :  34  Cost train:  5627.118264790457  Cost test:  5637.494259020411
Iteration :  35  Cost train:  5612.517487869592  Cost test:  5749.679576838301
Iteration :  36  Cost train:  5597.984125171894  Cost test:  5608.637534069709
Iteration :  37  Cost train:  5583.5178649112195  Cost test:  5720.374021362575
Iteration :  38  Cost train:  5569.1183967439665  Cost test:  5580.0479615307795
Iteration :  39  Cost train:  5554.785411762369  Cost test:  5691.3370493945495
Iteration :  40  Cost train:  5540.518602487852  Cost test:  5551.723070127253
Iteration :  41  Cost train:  5526.317662864428  Cost test:  5662.5661889706125
Iteration :  42  Cost train:  5512.182288252128  Cost test:  5523.660411424424
Iteration :  43  Cost train:  5498.112175420385  Cost test:  5634.05899091744
Iteration :  44  Cost train:  5484.107022541637  Cost test:  5495.857559618231
Iteration :  45  Cost train:  5470.166529184686  Cost test:  5605.813028641714
Iteration :  46  Cost train:  5456.290396308372  Cost test:  5468.31211132625
Iteration :  47  Cost train:  5442.478326255091  Cost test:  5577.8258979218745
Iteration :  48  Cost train:  5428.730022744311  Cost test:  5441.0216853806405
Iteration :  49  Cost train:  5415.045190866268  Cost test:  5550.095216701567
Iteration :  50  Cost train:  5401.423537075666  Cost test:  5413.9839226225085
Iteration :  51  Cost train:  5387.8647691853  Cost test:  5522.618624885039
Iteration :  52  Cost train:  5374.368596359795  Cost test:  5387.196485698925
Iteration :  53  Cost train:  5360.934729109333  Cost test:  5495.393784134666
Iteration :  54  Cost train:  5347.562879283504  Cost test:  5360.657058861335
Iteration :  55  Cost train:  5334.252760064916  Cost test:  5468.418377670155
Iteration :  56  Cost train:  5321.004085963175  Cost test:  5334.363347765795
Iteration :  57  Cost train:  5307.816572808841  Cost test:  5441.690110069279
Iteration :  58  Cost train:  5294.689937747113  Cost test:  5308.313079275439
Iteration :  59  Cost train:  5281.623899231764  Cost test:  5415.206707071366
Iteration :  60  Cost train:  5268.618177019241  Cost test:  5282.504001264268
Iteration :  61  Cost train:  5255.67249216254  Cost test:  5388.965915381511
Iteration :  62  Cost train:  5242.786567005183  Cost test:  5256.933882423346
Iteration :  63  Cost train:  5229.960125175256  Cost test:  5362.965502477495
Iteration :  64  Cost train:  5217.19289157951  Cost test:  5231.600512068152
Iteration :  65  Cost train:  5204.484592397422  Cost test:  5337.203256417859
Iteration :  66  Cost train:  5191.8349550752455  Cost test:  5206.501699948195
Iteration :  67  Cost train:  5179.243708320272  Cost test:  5311.67698565207
Iteration :  68  Cost train:  5166.710582094853  Cost test:  5181.635276058109
Iteration :  69  Cost train:  5154.235307610756  Cost test:  5286.384518832403
Iteration :  70  Cost train:  5141.817617323213  Cost test:  5156.999090450724
Iteration :  71  Cost train:  5129.457244925316  Cost test:  5261.323704627607
Iteration :  72  Cost train:  5117.153925342113  Cost test:  5132.5910130516795
Iteration :  73  Cost train:  5104.90739472501  Cost test:  5236.492411537894
Iteration :  74  Cost train:  5092.717390446261  Cost test:  5108.408933475528
Iteration :  75  Cost train:  5080.583651092998  Cost test:  5211.888527712314
Iteration :  76  Cost train:  5068.50591646181  Cost test:  5084.450760844371
Iteration :  77  Cost train:  5056.483927553168  Cost test:  5187.50996076727
Iteration :  78  Cost train:  5044.517426565645  Cost test:  5060.714423607252
Iteration :  79  Cost train:  5032.606156890584  Cost test:  5163.354637606842
Iteration :  80  Cost train:  5020.749863106589  Cost test:  5037.197869361458
Iteration :  81  Cost train:  5008.948290973779  Cost test:  5139.42050424496
Iteration :  82  Cost train:  4997.201187428637  Cost test:  5013.8990646758675
Iteration :  83  Cost train:  4985.5083005783845  Cost test:  5115.705525628929
Iteration :  84  Cost train:  4973.869379695576  Cost test:  4990.815994915662
Iteration :  85  Cost train:  4962.2841752127415  Cost test:  5092.207685464916
Iteration :  86  Cost train:  4950.752438717008  Cost test:  4967.9466640684595
Iteration :  87  Cost train:  4939.273922944711  Cost test:  5068.924986044648
Iteration :  88  Cost train:  4927.8483817762035  Cost test:  4945.28909457227
Iteration :  89  Cost train:  4916.47557023043  Cost test:  5045.855448074057
Iteration :  90  Cost train:  4905.155244459788  Cost test:  4922.841327145279
Iteration :  91  Cost train:  4893.887161744652  Cost test:  5022.997110503497
Iteration :  92  Cost train:  4882.671080488415  Cost test:  4900.601420616619
Iteration :  93  Cost train:  4871.506760212181  Cost test:  5000.348030359078
Iteration :  94  Cost train:  4860.393961549514  Cost test:  4878.567451759233
Iteration :  95  Cost train:  4849.332446241429  Cost test:  4977.906282576097
Iteration :  96  Cost train:  4838.321977131268  Cost test:  4856.737515123936
Iteration :  97  Cost train:  4827.362318159334  Cost test:  4955.669959833855
Iteration :  98  Cost train:  4816.453234358273  Cost test:  4835.109722875182
Iteration :  99  Cost train:  4805.59449184757  Cost test:  4933.637172391745
Iteration :  100  Cost train:  4794.785857828848  Cost test:  4813.6822046284715
Iteration :  101  Cost train:  4784.027100580656  Cost test:  4911.806047927262
Iteration :  102  Cost train:  4773.317989453551  Cost test:  4792.453107288967
Iteration :  103  Cost train:  4762.658294865189  Cost test:  4890.174731375107
Iteration :  104  Cost train:  4752.047788295286  Cost test:  4771.4205948917015
Iteration :  105  Cost train:  4741.486242280782  Cost test:  4868.741384768028
Iteration :  106  Cost train:  4730.973430410946  Cost test:  4750.582848443317
Iteration :  107  Cost train:  4720.509127322456  Cost test:  4847.504187079106
Iteration :  108  Cost train:  4710.0931086946075  Cost test:  4729.938065765354
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Iteration :  2003  Cost train:  2439.68211301274  Cost test:  2513.8419051864967
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Iteration :  2007  Cost train:  2439.623774285107  Cost test:  2513.784706806051
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Iteration :  2010  Cost train:  2439.5801308034006  Cost test:  2512.4329454949107
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Iteration :  2014  Cost train:  2439.5220851264485  Cost test:  2512.3882235685023
Iteration :  2015  Cost train:  2439.5075994839895  Cost test:  2513.670988151017
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Iteration :  2017  Cost train:  2439.4786588935062  Cost test:  2513.6426977337333
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Iteration :  2019  Cost train:  2439.4497590048313  Cost test:  2513.614462331681
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Iteration :  2936  Cost train:  2428.4675882771467  Cost test:  2503.5694357270136
Iteration :  2937  Cost train:  2428.4571250661133  Cost test:  2503.7135336830847
Iteration :  2938  Cost train:  2428.4466642876314  Cost test:  2503.552348580382
Iteration :  2939  Cost train:  2428.4362059405016  Cost test:  2503.695744105557
Iteration :  2940  Cost train:  2428.42575002353  Cost test:  2503.5352687350205
Iteration :  2941  Cost train:  2428.415296535522  Cost test:  2503.677965093994
Iteration :  2942  Cost train:  2428.404845475287  Cost test:  2503.5181961881017
Iteration :  2943  Cost train:  2428.3943968416365  Cost test:  2503.660196630462
Iteration :  2944  Cost train:  2428.383950633385  Cost test:  2503.501130936805
Iteration :  2945  Cost train:  2428.373506849349  Cost test:  2503.642438697108
Iteration :  2946  Cost train:  2428.363065488345  Cost test:  2503.484072978317
Iteration :  2947  Cost train:  2428.3526265491964  Cost test:  2503.6246912761526
Iteration :  2948  Cost train:  2428.3421900307253  Cost test:  2503.46702230983
Iteration :  2949  Cost train:  2428.331755931757  Cost test:  2503.6069543498943
Iteration :  2950  Cost train:  2428.3213242511197  Cost test:  2503.4499789285455
Iteration :  2951  Cost train:  2428.3108949876446  Cost test:  2503.5892279007066
Iteration :  2952  Cost train:  2428.300468140162  Cost test:  2503.43294283167
Iteration :  2953  Cost train:  2428.290043707509  Cost test:  2503.571511911038
Iteration :  2954  Cost train:  2428.279621688521  Cost test:  2503.4159140164165
Iteration :  2955  Cost train:  2428.269202082038  Cost test:  2503.553806363412
Iteration :  2956  Cost train:  2428.258784886901  Cost test:  2503.3988924800055
Iteration :  2957  Cost train:  2428.2483701019546  Cost test:  2503.536111240427
Iteration :  2958  Cost train:  2428.237957726044  Cost test:  2503.381878219662
Iteration :  2959  Cost train:  2428.2275477580174  Cost test:  2503.518426524754
Iteration :  2960  Cost train:  2428.2171401967257  Cost test:  2503.364871232619
Iteration :  2961  Cost train:  2428.2067350410216  Cost test:  2503.500752199137
Iteration :  2962  Cost train:  2428.1963322897595  Cost test:  2503.347871516114
Iteration :  2963  Cost train:  2428.1859319417968  Cost test:  2503.4830882463953
Iteration :  2964  Cost train:  2428.1755339959927  Cost test:  2503.3308790673905
Iteration :  2965  Cost train:  2428.1651384512083  Cost test:  2503.4654346494176
Iteration :  2966  Cost train:  2428.1547453063067  Cost test:  2503.3138938836983
Iteration :  2967  Cost train:  2428.144354560155  Cost test:  2503.447791391167
Iteration :  2968  Cost train:  2428.1339662116197  Cost test:  2503.2969159622908
Iteration :  2969  Cost train:  2428.1235802595716  Cost test:  2503.430158454675
Iteration :  2970  Cost train:  2428.113196702882  Cost test:  2503.2799453004295
Iteration :  2971  Cost train:  2428.102815540426  Cost test:  2503.412535823047
Iteration :  2972  Cost train:  2428.0924367710786  Cost test:  2503.2629818953783
Iteration :  2973  Cost train:  2428.08206039372  Cost test:  2503.394923479459
Iteration :  2974  Cost train:  2428.071686407229  Cost test:  2503.246025744408
Iteration :  2975  Cost train:  2428.0613148104894  Cost test:  2503.3773214071553
Iteration :  2976  Cost train:  2428.0509456023856  Cost test:  2503.229076844794
Iteration :  2977  Cost train:  2428.040578781803  Cost test:  2503.35972958945
Iteration :  2978  Cost train:  2428.0302143476324  Cost test:  2503.2121351938144
Iteration :  2979  Cost train:  2428.019852298763  Cost test:  2503.3421480097277
Iteration :  2980  Cost train:  2428.009492634089  Cost test:  2503.1952007887553
Iteration :  2981  Cost train:  2427.999135352504  Cost test:  2503.324576651441
Iteration :  2982  Cost train:  2427.988780452906  Cost test:  2503.1782736269047
Iteration :  2983  Cost train:  2427.9784279341934  Cost test:  2503.3070154981115
Iteration :  2984  Cost train:  2427.9680777952667  Cost test:  2503.1613537055555
Iteration :  2985  Cost train:  2427.9577300350297  Cost test:  2503.289464533328
Iteration :  2986  Cost train:  2427.9473846523865  Cost test:  2503.1444410220056
Iteration :  2987  Cost train:  2427.937041646245  Cost test:  2503.2719237407473
Iteration :  2988  Cost train:  2427.9267010155127  Cost test:  2503.1275355735556
Iteration :  2989  Cost train:  2427.9163627591015  Cost test:  2503.2543931040927
Iteration :  2990  Cost train:  2427.906026875924  Cost test:  2503.1106373575117
Iteration :  2991  Cost train:  2427.895693364895  Cost test:  2503.236872607156
Iteration :  2992  Cost train:  2427.885362224931  Cost test:  2503.0937463711825
Iteration :  2993  Cost train:  2427.875033454951  Cost test:  2503.2193622337927
Iteration :  2994  Cost train:  2427.8647070538746  Cost test:  2503.0768626118806
Iteration :  2995  Cost train:  2427.854383020625  Cost test:  2503.2018619679257
Iteration :  2996  Cost train:  2427.8440613541266  Cost test:  2503.059986076923
Iteration :  2997  Cost train:  2427.8337420533057  Cost test:  2503.1843717935435
Iteration :  2998  Cost train:  2427.8234251170898  Cost test:  2503.0431167636293
Iteration :  2999  Cost train:  2427.81311054441  Cost test:  2503.1668916946987
Iteration :  3000  Cost train:  2427.802798334197  Cost test:  2503.026254669323
Iteration :  3001  Cost train:  2427.792488485386  Cost test:  2503.1494216555097
Iteration :  3002  Cost train:  2427.7821809969114  Cost test:  2503.00939979133
Iteration :  3003  Cost train:  2427.771875867712  Cost test:  2503.1319616601577
Iteration :  3004  Cost train:  2427.761573096726  Cost test:  2502.99255212698
Iteration :  3005  Cost train:  2427.7512726828954  Cost test:  2503.1145116928897
Iteration :  3006  Cost train:  2427.740974625163  Cost test:  2502.9757116736055
Iteration :  3007  Cost train:  2427.730678922473  Cost test:  2503.0970717380137
Iteration :  3008  Cost train:  2427.7203855737735  Cost test:  2502.9588784285424
Iteration :  3009  Cost train:  2427.7100945780116  Cost test:  2503.0796417799024
Iteration :  3010  Cost train:  2427.699805934139  Cost test:  2502.9420523891276
Iteration :  3011  Cost train:  2427.689519641107  Cost test:  2503.0622218029916
Iteration :  3012  Cost train:  2427.6792356978694  Cost test:  2502.925233552703
Iteration :  3013  Cost train:  2427.668954103382  Cost test:  2503.044811791778
Iteration :  3014  Cost train:  2427.658674856603  Cost test:  2502.908421916611
Iteration :  3015  Cost train:  2427.6483979564905  Cost test:  2503.0274117308218
Iteration :  3016  Cost train:  2427.638123402006  Cost test:  2502.8916174781984
Iteration :  3017  Cost train:  2427.6278511921128  Cost test:  2503.0100216047417
Iteration :  3018  Cost train:  2427.6175813257746  Cost test:  2502.874820234813
Iteration :  3019  Cost train:  2427.607313801958  Cost test:  2502.9926413982216
Iteration :  3020  Cost train:  2427.5970486196306  Cost test:  2502.8580301838047
Iteration :  3021  Cost train:  2427.5867857777625  Cost test:  2502.9752710960042
Iteration :  3022  Cost train:  2427.576525275326  Cost test:  2502.841247322526
Iteration :  3023  Cost train:  2427.566267111292  Cost test:  2502.9579106828915
Iteration :  3024  Cost train:  2427.556011284637  Cost test:  2502.8244716483323
Iteration :  3025  Cost train:  2427.545757794337  Cost test:  2502.9405601437466
Iteration :  3026  Cost train:  2427.535506639371  Cost test:  2502.807703158579
Iteration :  3027  Cost train:  2427.525257818718  Cost test:  2502.9232194634924
Iteration :  3028  Cost train:  2427.51501133136  Cost test:  2502.7909418506247
Iteration :  3029  Cost train:  2427.50476717628  Cost test:  2502.905888627112
Iteration :  3030  Cost train:  2427.494525352463  Cost test:  2502.774187721829
Iteration :  3031  Cost train:  2427.484285858896  Cost test:  2502.8885676196455
Iteration :  3032  Cost train:  2427.474048694567  Cost test:  2502.7574407695543
Iteration :  3033  Cost train:  2427.463813858466  Cost test:  2502.8712564261928
Iteration :  3034  Cost train:  2427.453581349584  Cost test:  2502.740700991164
Iteration :  3035  Cost train:  2427.443351166915  Cost test:  2502.853955031912
Iteration :  3036  Cost train:  2427.4331233094535  Cost test:  2502.7239683840216
Iteration :  3037  Cost train:  2427.422897776195  Cost test:  2502.836663422018
Iteration :  3038  Cost train:  2427.412674566139  Cost test:  2502.7072429454943
Iteration :  3039  Cost train:  2427.4024536782845  Cost test:  2502.8193815817845
Iteration :  3040  Cost train:  2427.392235111632  Cost test:  2502.6905246729484
Iteration :  3041  Cost train:  2427.3820188651857  Cost test:  2502.8021094965425
Iteration :  3042  Cost train:  2427.3718049379495  Cost test:  2502.6738135637534
Iteration :  3043  Cost train:  2427.3615933289284  Cost test:  2502.784847151678
Iteration :  3044  Cost train:  2427.351384037131  Cost test:  2502.657109615278
Iteration :  3045  Cost train:  2427.3411770615667  Cost test:  2502.7675945326364
Iteration :  3046  Cost train:  2427.3309724012456  Cost test:  2502.6404128248937
Iteration :  3047  Cost train:  2427.32077005518  Cost test:  2502.7503516249153
Iteration :  3048  Cost train:  2427.3105700223846  Cost test:  2502.6237231899713
Iteration :  3049  Cost train:  2427.300372301873  Cost test:  2502.733118414072
Iteration :  3050  Cost train:  2427.290176892663  Cost test:  2502.6070407078832
Iteration :  3051  Cost train:  2427.2799837937737  Cost test:  2502.7158948857177
Iteration :  3052  Cost train:  2427.269793004224  Cost test:  2502.5903653760033
Iteration :  3053  Cost train:  2427.2596045230366  Cost test:  2502.698681025517
Iteration :  3054  Cost train:  2427.249418349233  Cost test:  2502.573697191705
Iteration :  3055  Cost train:  2427.2392344818386  Cost test:  2502.681476819193
Iteration :  3056  Cost train:  2427.22905291988  Cost test:  2502.5570361523623
Iteration :  3057  Cost train:  2427.2188736623834  Cost test:  2502.6642822525196
Iteration :  3058  Cost train:  2427.2086967083783  Cost test:  2502.540382255351
Iteration :  3059  Cost train:  2427.1985220568954  Cost test:  2502.647097311328
Iteration :  3060  Cost train:  2427.188349706966  Cost test:  2502.523735498047
Iteration :  3061  Cost train:  2427.178179657625  Cost test:  2502.6299219815
Iteration :  3062  Cost train:  2427.168011907906  Cost test:  2502.507095877824
Iteration :  3063  Cost train:  2427.157846456845  Cost test:  2502.6127562489737
Iteration :  3064  Cost train:  2427.1476833034812  Cost test:  2502.4904633920605
Iteration :  3065  Cost train:  2427.1375224468525  Cost test:  2502.595600099739
Iteration :  3066  Cost train:  2427.1273638860007  Cost test:  2502.473838038132
Iteration :  3067  Cost train:  2427.117207619967  Cost test:  2502.5784535198386
Iteration :  3068  Cost train:  2427.107053647796  Cost test:  2502.457219813414
Iteration :  3069  Cost train:  2427.096901968532  Cost test:  2502.561316495369
Iteration :  3070  Cost train:  2427.086752581222  Cost test:  2502.4406087152856
Iteration :  3071  Cost train:  2427.0766054849128  Cost test:  2502.5441890124766
Iteration :  3072  Cost train:  2427.0664606786545  Cost test:  2502.4240047411213
Iteration :  3073  Cost train:  2427.056318161498  Cost test:  2502.5270710573627
Iteration :  3074  Cost train:  2427.0461779324946  Cost test:  2502.407407888298
Iteration :  3075  Cost train:  2427.036039990698  Cost test:  2502.5099626162773
Iteration :  3076  Cost train:  2427.0259043351634  Cost test:  2502.390818154193
Iteration :  3077  Cost train:  2427.015770964947  Cost test:  2502.4928636755235
Iteration :  3078  Cost train:  2427.0056398791057  Cost test:  2502.3742355361824
Iteration :  3079  Cost train:  2426.9955110766996  Cost test:  2502.475774221456
Iteration :  3080  Cost train:  2426.985384556788  Cost test:  2502.357660031641
Iteration :  3081  Cost train:  2426.975260318433  Cost test:  2502.4586942404776
Iteration :  3082  Cost train:  2426.965138360698  Cost test:  2502.341091637946
Iteration :  3083  Cost train:  2426.9550186826477  Cost test:  2502.4416237190435
Iteration :  3084  Cost train:  2426.9449012833466  Cost test:  2502.3245303524727
Iteration :  3085  Cost train:  2426.9347861618626  Cost test:  2502.424562643659
Iteration :  3086  Cost train:  2426.9246733172645  Cost test:  2502.3079761725958
Iteration :  3087  Cost train:  2426.9145627486214  Cost test:  2502.4075110008785
Iteration :  3088  Cost train:  2426.9044544550047  Cost test:  2502.291429095689
Iteration :  3089  Cost train:  2426.8943484354872  Cost test:  2502.390468777306
Iteration :  3090  Cost train:  2426.8842446891417  Cost test:  2502.274889119127
Iteration :  3091  Cost train:  2426.874143215044  Cost test:  2502.373435959595
Iteration :  3092  Cost train:  2426.8640440122713  Cost test:  2502.258356240283
Iteration :  3093  Cost train:  2426.853947079899  Cost test:  2502.356412534448
Iteration :  3094  Cost train:  2426.8438524170083  Cost test:  2502.2418304565285
Iteration :  3095  Cost train:  2426.833760022678  Cost test:  2502.339398488616
Iteration :  3096  Cost train:  2426.82366989599  Cost test:  2502.2253117652367
Iteration :  3097  Cost train:  2426.8135820360276  Cost test:  2502.3223938088986
Iteration :  3098  Cost train:  2426.8034964418744  Cost test:  2502.208800163777
Iteration :  3099  Cost train:  2426.7934131126162  Cost test:  2502.3053984821427
Iteration :  3100  Cost train:  2426.783332047339  Cost test:  2502.1922956495214
Iteration :  3101  Cost train:  2426.7732532451314  Cost test:  2502.2884124952434
Iteration :  3102  Cost train:  2426.7631767050825  Cost test:  2502.1757982198383
Iteration :  3103  Cost train:  2426.7531024262817  Cost test:  2502.271435835144
Iteration :  3104  Cost train:  2426.743030407822  Cost test:  2502.1593078720957
Iteration :  3105  Cost train:  2426.732960648795  Cost test:  2502.2544684888344
Iteration :  3106  Cost train:  2426.722893148296  Cost test:  2502.1428246036608
Iteration :  3107  Cost train:  2426.7128279054205  Cost test:  2502.2375104433513
Iteration :  3108  Cost train:  2426.7027649192637  Cost test:  2502.126348411901
Iteration :  3109  Cost train:  2426.692704188924  Cost test:  2502.220561685778
Iteration :  3110  Cost train:  2426.6826457135007  Cost test:  2502.10987929418
Iteration :  3111  Cost train:  2426.6725894920946  Cost test:  2502.2036222032452
Iteration :  3112  Cost train:  2426.662535523806  Cost test:  2502.093417247863
Iteration :  3113  Cost train:  2426.652483807739  Cost test:  2502.186691982929
Iteration :  3114  Cost train:  2426.6424343429953  Cost test:  2502.076962270311
Iteration :  3115  Cost train:  2426.6323871286822  Cost test:  2502.169771012051
Iteration :  3116  Cost train:  2426.6223421639047  Cost test:  2502.0605143588873
Iteration :  3117  Cost train:  2426.612299447771  Cost test:  2502.1528592778795
Iteration :  3118  Cost train:  2426.602258979389  Cost test:  2502.044073510951
Iteration :  3119  Cost train:  2426.5922207578687  Cost test:  2502.135956767727
Iteration :  3120  Cost train:  2426.5821847823213  Cost test:  2502.0276397238613
Iteration :  3121  Cost train:  2426.572151051859  Cost test:  2502.119063468952
Iteration :  3122  Cost train:  2426.5621195655945  Cost test:  2502.011212994975
Iteration :  3123  Cost train:  2426.5520903226434  Cost test:  2502.1021793689574
Iteration :  3124  Cost train:  2426.5420633221197  Cost test:  2501.9947933216486
Iteration :  3125  Cost train:  2426.5320385631426  Cost test:  2502.0853044551905
Iteration :  3126  Cost train:  2426.522016044828  Cost test:  2501.978380701237
Iteration :  3127  Cost train:  2426.511995766295  Cost test:  2502.068438715143
Iteration :  3128  Cost train:  2426.501977726665  Cost test:  2501.961975131092
Iteration :  3129  Cost train:  2426.4919619250586  Cost test:  2502.051582136352
Iteration :  3130  Cost train:  2426.4819483605984  Cost test:  2501.945576608565
Iteration :  3131  Cost train:  2426.4719370324083  Cost test:  2502.0347347063953
Iteration :  3132  Cost train:  2426.4619279396125  Cost test:  2501.9291851310068
Iteration :  3133  Cost train:  2426.451921081337  Cost test:  2502.0178964128977
Iteration :  3134  Cost train:  2426.441916456709  Cost test:  2501.912800695764
Iteration :  3135  Cost train:  2426.4319140648568  Cost test:  2502.0010672435246
Iteration :  3136  Cost train:  2426.421913904909  Cost test:  2501.8964233001843
Iteration :  3137  Cost train:  2426.411915975996  Cost test:  2501.9842471859865
Convergence Achieved at  3137.0  iteration
Cost Minima Found :  2426.411915975996
Betas : 
X0              50.915400
T1              14.514373
RH_1           107.184012
T2              51.290024
RH_2           -26.769808
T3              28.283545
RH_3            66.023806
T4               4.202032
RH_4            48.741698
T5              -5.829256
RH_5            12.517115
RH_6           -63.599637
T7              -8.030460
RH_7           -50.004085
T8              12.209429
RH_8          -107.811812
RH_9           -39.245345
T_out           80.359908
Press_mm_hg     73.482860
RH_out        -355.935002
Windspeed       58.198461
Tdewpoint        3.312146
dtype: float64

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_optimum['Iteration'],
                            y=graph_optimum['Cost_train'],
                            name='Train',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_optimum['Iteration'],
                            y=graph_optimum['Cost_test'],
                            name='Test',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration with Alpha= 1 and Criteria= 0.01 ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

Experiment with Randomly picked variables(Experiment 3)¶

x_train_sampled=x_train.sample(10,axis=1,random_state=48)

x_test_sampled=x_test.sample(10,axis=1,random_state=48)

x_train_sampled.columns

Index(['T1', 'T5', 'T3', 'T4', 'RH_4', 'RH_7', 'Press_mm_hg', 'T2', 'RH_6',
       'RH_5'],
      dtype='object')

x_train_sampled.insert(0,'X0',1)
x_test_sampled.insert(0,'X0',1)

initial_params,params,graph_sampled=batch_gradient_descent_v3('lr',x_train_sampled,y_train,x_test_sampled,y_test,1,0.01,1000000)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  5942.962885197807  Cost test:  5950.597127651988
Iteration :  3  Cost train:  5748.671814453054  Cost test:  5887.37362235734
Iteration :  4  Cost train:  5565.360730585057  Cost test:  5576.738672772538
Iteration :  5  Cost train:  5392.4088823279035  Cost test:  5527.444986878336
Iteration :  6  Cost train:  5229.230613205154  Cost test:  5244.13920716433
Iteration :  7  Cost train:  5075.27337740875  Cost test:  5206.849568040618
Iteration :  8  Cost train:  4930.015867852118  Cost test:  4948.254147530766
Iteration :  9  Cost train:  4792.966250055819  Cost test:  4921.276721516269
Iteration :  10  Cost train:  4663.660495882788  Cost test:  4685.038890273218
Iteration :  11  Cost train:  4541.660811477061  Cost test:  4666.888815475088
Iteration :  12  Cost train:  4426.554154080981  Cost test:  4450.893839611524
Iteration :  13  Cost train:  4317.950832705559  Cost test:  4440.269293136768
Iteration :  14  Cost train:  4215.48318791367  Cost test:  4242.615477830107
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Iteration :  495  Cost train:  2486.7554959380122  Cost test:  2557.4059228105943
Iteration :  496  Cost train:  2486.737255654698  Cost test:  2557.382928060849
Iteration :  497  Cost train:  2486.7190701524964  Cost test:  2557.360147915185
Iteration :  498  Cost train:  2486.7009392577947  Cost test:  2557.3372818371363
Iteration :  499  Cost train:  2486.68286279753  Cost test:  2557.314621378522
Iteration :  500  Cost train:  2486.6648405991878  Cost test:  2557.291882983288
Iteration :  501  Cost train:  2486.6468724908004  Cost test:  2557.2693417120345
Iteration :  502  Cost train:  2486.6289583009457  Cost test:  2557.2467300292515
Iteration :  503  Cost train:  2486.6110978587444  Cost test:  2557.224307436646
Iteration :  504  Cost train:  2486.5932909938597  Cost test:  2557.201821513649
Iteration :  505  Cost train:  2486.5755375364934  Cost test:  2557.179517082696
Iteration :  506  Cost train:  2486.5578373173876  Cost test:  2557.157155983746
Iteration :  507  Cost train:  2486.540190167818  Cost test:  2557.1349691898595
Iteration :  508  Cost train:  2486.522595919598  Cost test:  2557.112731995415
Iteration :  509  Cost train:  2486.5050544050728  Cost test:  2557.0906623070755
Iteration :  510  Cost train:  2486.487565457119  Cost test:  2557.068548113098
Iteration :  511  Cost train:  2486.4701289091436  Cost test:  2557.0465949924674
Iteration :  512  Cost train:  2486.452744595081  Cost test:  2557.024602909772
Iteration :  513  Cost train:  2486.4354123493918  Cost test:  2557.002765813273
Iteration :  514  Cost train:  2486.418132007063  Cost test:  2556.980894966909
Iteration :  515  Cost train:  2486.400903403602  Cost test:  2556.959173345773
Iteration :  516  Cost train:  2486.3837263750397  Cost test:  2556.937422874439
Iteration :  517  Cost train:  2486.3666007579263  Cost test:  2556.915816175216
Iteration :  518  Cost train:  2486.3495263893296  Cost test:  2556.8941852307103
Iteration :  519  Cost train:  2486.3325031068352  Cost test:  2556.8726928957567
Iteration :  520  Cost train:  2486.3155307485413  Cost test:  2556.851180642451
Iteration :  521  Cost train:  2486.2986091530615  Cost test:  2556.829802110379
Iteration :  522  Cost train:  2486.281738159519  Cost test:  2556.808407724728
Iteration :  523  Cost train:  2486.2649176075497  Cost test:  2556.7871424308382
Iteration :  524  Cost train:  2486.2481473372945  Cost test:  2556.7658651009083
Iteration :  525  Cost train:  2486.231427189404  Cost test:  2556.744712477587
Iteration :  526  Cost train:  2486.214757005031  Cost test:  2556.7235514026156
Iteration :  527  Cost train:  2486.1981366258346  Cost test:  2556.7025108797156
Iteration :  528  Cost train:  2486.1815658939745  Cost test:  2556.6814652696935
Iteration :  529  Cost train:  2486.1650446521107  Cost test:  2556.660536274887
Iteration :  530  Cost train:  2486.148572743402  Cost test:  2556.639605350158
Iteration :  531  Cost train:  2486.1321500115046  Cost test:  2556.6187873092726
Iteration :  532  Cost train:  2486.11577630057  Cost test:  2556.5979703001613
Iteration :  533  Cost train:  2486.0994514552444  Cost test:  2556.5772626374924
Iteration :  534  Cost train:  2486.083175320665  Cost test:  2556.5565587839474
Iteration :  535  Cost train:  2486.0669477424617  Cost test:  2556.535960922552
Iteration :  536  Cost train:  2486.0507685667526  Cost test:  2556.5153694738096
Iteration :  537  Cost train:  2486.034637640143  Cost test:  2556.4948808357844
Iteration :  538  Cost train:  2486.0185548097265  Cost test:  2556.474401050048
Iteration :  539  Cost train:  2486.00251992308  Cost test:  2556.4540210567898
Iteration :  540  Cost train:  2485.986532828263  Cost test:  2556.43365220093
Iteration :  541  Cost train:  2485.9705933738173  Cost test:  2556.413380273375
Iteration :  542  Cost train:  2485.9547014087657  Cost test:  2556.3931216226415
Iteration :  543  Cost train:  2485.9388567826086  Cost test:  2556.3729571815
Iteration :  544  Cost train:  2485.9230593453226  Cost test:  2556.352808019251
Iteration :  545  Cost train:  2485.907308947362  Cost test:  2556.3327504852177
Iteration :  546  Cost train:  2485.8916054396527  Cost test:  2556.312710102661
Iteration :  547  Cost train:  2485.8759486735958  Cost test:  2556.292758896618
Iteration :  548  Cost train:  2485.8603385010615  Cost test:  2556.2728265925693
Iteration :  549  Cost train:  2485.8447747743894  Cost test:  2556.2529811357736
Iteration :  550  Cost train:  2485.8292573463896  Cost test:  2556.2331562164222
Iteration :  551  Cost train:  2485.813786070335  Cost test:  2556.213415930683
Iteration :  552  Cost train:  2485.7983607999668  Cost test:  2556.193697709374
Iteration :  553  Cost train:  2485.7829813894887  Cost test:  2556.1740620172172
Iteration :  554  Cost train:  2485.767647693566  Cost test:  2556.1544498142434
Iteration :  555  Cost train:  2485.7523595673256  Cost test:  2556.1349181390674
Iteration :  556  Cost train:  2485.737116866352  Cost test:  2556.1154112814697
Iteration :  557  Cost train:  2485.7219194466907  Cost test:  2556.0959830476895
Iteration :  558  Cost train:  2485.7067671648406  Cost test:  2556.0765808690694
Iteration :  559  Cost train:  2485.691659877756  Cost test:  2556.057255502253
Iteration :  560  Cost train:  2485.6765974428454  Cost test:  2556.0379573425944
Iteration :  561  Cost train:  2485.661579717969  Cost test:  2556.018734269589
Iteration :  562  Cost train:  2485.6466065614372  Cost test:  2555.9995394750895
Iteration :  563  Cost train:  2485.63167783201  Cost test:  2555.980418124138
Iteration :  564  Cost train:  2485.616793388895  Cost test:  2555.9613260470437
Iteration :  565  Cost train:  2485.6019530917456  Cost test:  2555.942305847899
Iteration :  566  Cost train:  2485.5871568006605  Cost test:  2555.9233158463576
Iteration :  567  Cost train:  2485.5724043761825  Cost test:  2555.9043962303817
Iteration :  568  Cost train:  2485.557695679295  Cost test:  2555.8855076682908
Iteration :  569  Cost train:  2485.543030571424  Cost test:  2555.8666880685532
Iteration :  570  Cost train:  2485.528408914432  Cost test:  2555.8479003154252
Iteration :  571  Cost train:  2485.5138305706228  Cost test:  2555.8291801667906
Iteration :  572  Cost train:  2485.4992954027334  Cost test:  2555.8104925976177
Iteration :  573  Cost train:  2485.4848032739383  Cost test:  2555.791871336831
Iteration :  574  Cost train:  2485.470354047844  Cost test:  2555.7732833319633
Iteration :  575  Cost train:  2485.4559475884907  Cost test:  2555.754760397724
Iteration :  576  Cost train:  2485.441583760349  Cost test:  2555.7362713427474
Iteration :  577  Cost train:  2485.427262428319  Cost test:  2555.7178461757853
Iteration :  578  Cost train:  2485.4129834577293  Cost test:  2555.6994554614053
Iteration :  579  Cost train:  2485.398746714335  Cost test:  2555.6811275045447
Iteration :  580  Cost train:  2485.384552064317  Cost test:  2555.662834526482
Iteration :  581  Cost train:  2485.370399374281  Cost test:  2555.6446032247036
Iteration :  582  Cost train:  2485.3562885112538  Cost test:  2555.6264073835873
Iteration :  583  Cost train:  2485.342219342686  Cost test:  2555.6082721840853
Iteration :  584  Cost train:  2485.328191736446  Cost test:  2555.590172885355
Iteration :  585  Cost train:  2485.3142055608228  Cost test:  2555.5721332375906
Iteration :  586  Cost train:  2485.3002606845234  Cost test:  2555.554129891401
Iteration :  587  Cost train:  2485.286356976668  Cost test:  2555.5361852471506
Iteration :  588  Cost train:  2485.2724943067947  Cost test:  2555.518277268283
Iteration :  589  Cost train:  2485.2586725448537  Cost test:  2555.5004270816835
Iteration :  590  Cost train:  2485.2448915612076  Cost test:  2555.482613889456
Iteration :  591  Cost train:  2485.23115122663  Cost test:  2555.4648576170453
Iteration :  592  Cost train:  2485.217451412305  Cost test:  2555.4471386352343
Iteration :  593  Cost train:  2485.2037919898235  Cost test:  2555.42947573599
Iteration :  594  Cost train:  2485.190172831184  Cost test:  2555.411850392749
Iteration :  595  Cost train:  2485.176593808792  Cost test:  2555.3942803281207
Iteration :  596  Cost train:  2485.163054795455  Cost test:  2555.3767480559063
Iteration :  597  Cost train:  2485.149555664386  Cost test:  2555.359270289851
Iteration :  598  Cost train:  2485.1360962891986  Cost test:  2555.3418305253476
Iteration :  599  Cost train:  2485.1226765439073  Cost test:  2555.3244445243554
Iteration :  600  Cost train:  2485.109296302926  Cost test:  2555.307096708409
Iteration :  601  Cost train:  2485.095955441067  Cost test:  2555.2898019415297
Iteration :  602  Cost train:  2485.0826538335386  Cost test:  2555.2725455190807
Iteration :  603  Cost train:  2485.0693913559458  Cost test:  2555.255341457949
Iteration :  604  Cost train:  2485.056167884288  Cost test:  2555.238175877967
Iteration :  605  Cost train:  2485.042983294955  Cost test:  2555.221061996821
Iteration :  606  Cost train:  2485.0298374647314  Cost test:  2555.2039867122458
Iteration :  607  Cost train:  2485.016730270792  Cost test:  2555.1869624879464
Iteration :  608  Cost train:  2485.0036615906997  Cost test:  2555.1699769556276
Iteration :  609  Cost train:  2484.9906313024057  Cost test:  2555.1530418676784
Iteration :  610  Cost train:  2484.9776392842496  Cost test:  2555.1361455483197
Iteration :  611  Cost train:  2484.9646854149546  Cost test:  2555.119299078878
Iteration :  612  Cost train:  2484.9517695736295  Cost test:  2555.102491436982
Iteration :  613  Cost train:  2484.9388916397666  Cost test:  2555.0857330708745
Iteration :  614  Cost train:  2484.926051493239  Cost test:  2555.069013574692
Iteration :  615  Cost train:  2484.9132490143015  Cost test:  2555.0523427994235
Iteration :  616  Cost train:  2484.9004840835883  Cost test:  2555.035710920902
Iteration :  617  Cost train:  2484.8877565821117  Cost test:  2555.0191272266666
Iteration :  618  Cost train:  2484.8750663912615  Cost test:  2555.0025824414033
Iteration :  619  Cost train:  2484.8624133928033  Cost test:  2554.9860853210926
Iteration :  620  Cost train:  2484.849797468878  Cost test:  2554.969627108285
Iteration :  621  Cost train:  2484.8372185019984  Cost test:  2554.9532160574936
Iteration :  622  Cost train:  2484.8246763750526  Cost test:  2554.9368438998977
Iteration :  623  Cost train:  2484.8121709712964  Cost test:  2554.92051841693
Iteration :  624  Cost train:  2484.7997021743595  Cost test:  2554.904231800814
Iteration :  625  Cost train:  2484.7872698682368  Cost test:  2554.887991386687
Iteration :  626  Cost train:  2484.7748739372937  Cost test:  2554.8717898017912
Iteration :  627  Cost train:  2484.7625142662605  Cost test:  2554.8556339602374
Iteration :  628  Cost train:  2484.750190740234  Cost test:  2554.839516899732
Iteration :  629  Cost train:  2484.7379032446734  Cost test:  2554.8234451372005
Iteration :  630  Cost train:  2484.7256516654043  Cost test:  2554.8074120976494
Iteration :  631  Cost train:  2484.71343588861  Cost test:  2554.791423923308
Iteration :  632  Cost train:  2484.7012558008387  Cost test:  2554.775474404626
Iteration :  633  Cost train:  2484.689111288995  Cost test:  2554.759569330359
Iteration :  634  Cost train:  2484.677002240343  Cost test:  2554.7437028357795
Iteration :  635  Cost train:  2484.6649285425055  Cost test:  2554.727880376189
Iteration :  636  Cost train:  2484.65289008346  Cost test:  2554.712096412225
Iteration :  637  Cost train:  2484.6408867515393  Cost test:  2554.696356084625
Iteration :  638  Cost train:  2484.6289184354305  Cost test:  2554.6806541610376
Iteration :  639  Cost train:  2484.6169850241736  Cost test:  2554.6649954854543
Iteration :  640  Cost train:  2484.6050864071603  Cost test:  2554.6493751152157
Iteration :  641  Cost train:  2484.5932224741323  Cost test:  2554.6337976143823
Iteration :  642  Cost train:  2484.581393115182  Cost test:  2554.6182583136447
Iteration :  643  Cost train:  2484.5695982207485  Cost test:  2554.602761512997
Iteration :  644  Cost train:  2484.5578376816197  Cost test:  2554.5873028010633
Iteration :  645  Cost train:  2484.546111388929  Cost test:  2554.571886228733
Iteration :  646  Cost train:  2484.5344192341554  Cost test:  2554.5565076280222
Iteration :  647  Cost train:  2484.5227611091213  Cost test:  2554.541170814835
Iteration :  648  Cost train:  2484.5111369059923  Cost test:  2554.5258718508535
Iteration :  649  Cost train:  2484.499546517275  Cost test:  2554.5106143303187
Iteration :  650  Cost train:  2484.4879898358195  Cost test:  2554.495394531633
Iteration :  651  Cost train:  2484.476466754811  Cost test:  2554.480215839939
Iteration :  652  Cost train:  2484.4649771677773  Cost test:  2554.465074738144
Iteration :  653  Cost train:  2484.453520968582  Cost test:  2554.44997441415
Iteration :  654  Cost train:  2484.4420980514255  Cost test:  2554.434911543843
Iteration :  655  Cost train:  2484.430708310843  Cost test:  2554.4198891290716
Iteration :  656  Cost train:  2484.4193516417045  Cost test:  2554.4049040278264
Iteration :  657  Cost train:  2484.408027939213  Cost test:  2554.3899590664546
Iteration :  658  Cost train:  2484.396737098905  Cost test:  2554.375051274792
Iteration :  659  Cost train:  2484.3854790166456  Cost test:  2554.3601833136427
Iteration :  660  Cost train:  2484.374253588632  Cost test:  2554.345352375008
Iteration :  661  Cost train:  2484.3630607113905  Cost test:  2554.3305609635413
Iteration :  662  Cost train:  2484.351900281773  Cost test:  2554.3158064242775
Iteration :  663  Cost train:  2484.340772196961  Cost test:  2554.3010911145807
Iteration :  664  Cost train:  2484.329676354462  Cost test:  2554.2864125239025
Iteration :  665  Cost train:  2484.3186126521064  Cost test:  2554.2717728706807
Iteration :  666  Cost train:  2484.3075809880497  Cost test:  2554.2571697806525
Iteration :  667  Cost train:  2484.2965812607695  Cost test:  2554.2426053412187
Iteration :  668  Cost train:  2484.2856133690657  Cost test:  2554.2280773067314
Iteration :  669  Cost train:  2484.2746772120595  Cost test:  2554.213587640994
Iteration :  670  Cost train:  2484.2637726891917  Cost test:  2554.1991342197393
Iteration :  671  Cost train:  2484.25289970022  Cost test:  2554.184718890195
Iteration :  672  Cost train:  2484.2420581452234  Cost test:  2554.170339642645
Iteration :  673  Cost train:  2484.231247924594  Cost test:  2554.155998214365
Iteration :  674  Cost train:  2484.2204689390414  Cost test:  2554.141692703749
Iteration :  675  Cost train:  2484.2097210895904  Cost test:  2554.12742474437
Iteration :  676  Cost train:  2484.1990042775788  Cost test:  2554.1131925366512
Iteration :  677  Cost train:  2484.1883184046574  Cost test:  2554.098997616362
Iteration :  678  Cost train:  2484.1776633727873  Cost test:  2554.08483828022
Iteration :  679  Cost train:  2484.167039084243  Cost test:  2554.070715971751
Iteration :  680  Cost train:  2484.156445441607  Cost test:  2554.056629078558
Iteration :  681  Cost train:  2484.1458823477715  Cost test:  2554.042578957169
Iteration :  682  Cost train:  2484.135349705935  Cost test:  2554.0285640809693
Iteration :  683  Cost train:  2484.124847419605  Cost test:  2554.01458572444
Iteration :  684  Cost train:  2484.114375392593  Cost test:  2554.0006424419294
Iteration :  685  Cost train:  2484.103933529017  Cost test:  2553.9867354305443
Iteration :  686  Cost train:  2484.093521733297  Cost test:  2553.9728633210507
Iteration :  687  Cost train:  2484.0831399101576  Cost test:  2553.9590272375885
Iteration :  688  Cost train:  2484.072787964625  Cost test:  2553.945225883054
Iteration :  689  Cost train:  2484.0624658020265  Cost test:  2553.9314603127746
Iteration :  690  Cost train:  2484.052173327989  Cost test:  2553.917729297733
Iteration :  691  Cost train:  2484.041910448439  Cost test:  2553.904033828367
Iteration :  692  Cost train:  2484.0316770696  Cost test:  2553.8903727399256
Iteration :  693  Cost train:  2484.021473097996  Cost test:  2553.87674696166
Iteration :  694  Cost train:  2484.011298440443  Cost test:  2553.8631553894834
Iteration :  695  Cost train:  2484.0011530040565  Cost test:  2553.849598894949
Iteration :  696  Cost train:  2483.991036696243  Cost test:  2553.8360764312374
Iteration :  697  Cost train:  2483.980949424704  Cost test:  2553.822588815498
Iteration :  698  Cost train:  2483.970891097434  Cost test:  2553.809135054971
Iteration :  699  Cost train:  2483.9608616227183  Cost test:  2553.7957159155076
Iteration :  700  Cost train:  2483.950860909134  Cost test:  2553.782330455386
Iteration :  701  Cost train:  2483.940888865546  Cost test:  2553.768979392088
Convergence Achieved at  701.0  iteration
Cost Minima Found :  2483.940888865546
Betas : 
X0              37.906850
T1               7.003366
T5               2.273038
T3              10.306242
T4               5.863749
RH_4             6.879274
RH_7           -17.691637
Press_mm_hg     56.485115
T2              17.272358
RH_6          -116.389204
RH_5            -2.478357
dtype: float64

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_optimum['Iteration'],
                            y=graph_optimum['Cost_train'],
                            name='Train_optimum',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_optimum['Iteration'],
                            y=graph_optimum['Cost_test'],
                            name='Test_optimum',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_sampled['Iteration'],
                            y=graph_sampled['Cost_train'],
                            name='Test_sampled',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_sampled['Iteration'],
                            y=graph_sampled['Cost_test'],
                            name='Test_sampled',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

Picking 10 best features(Experiment 4)¶

x_train_pick=x_train[['Windspeed','RH_out','RH_6','RH_8','RH_1','T1','T3','RH_3','T5','T_out']]
x_test_pick=x_test[['Windspeed','RH_out','RH_6','RH_8','RH_1','T1','T3','RH_3','T5','T_out']]

x_train_pick.insert(0,'X0',1)
x_test_pick.insert(0,'X0',1)

initial_params,params,graph_pick=batch_gradient_descent_v3('lr',x_train_pick,y_train,x_test_pick,y_test,1,0.01,1000000)

Iteration :  1  Cost train:  6148.891891891892  Cost test:  6291.477477477478
Iteration :  2  Cost train:  2514.9881917654106  Cost test:  2587.47364683478
Iteration :  3  Cost train:  2512.2733484705627  Cost test:  2586.6098905379736
Iteration :  4  Cost train:  2512.1172778129767  Cost test:  2586.3954437162292
Iteration :  5  Cost train:  2511.963477665531  Cost test:  2586.2339750847477
Iteration :  6  Cost train:  2511.810145278055  Cost test:  2586.0716521181425
Iteration :  7  Cost train:  2511.657277783599  Cost test:  2585.909852941466
Iteration :  8  Cost train:  2511.5048735888195  Cost test:  2585.748539253431
Iteration :  9  Cost train:  2511.352931106777  Cost test:  2585.5877103897706
Iteration :  10  Cost train:  2511.201448756023  Cost test:  2585.4273646929887
Iteration :  11  Cost train:  2511.0504249605815  Cost test:  2585.2675005376923
Iteration :  12  Cost train:  2510.899858149929  Cost test:  2585.1081163033573
Iteration :  13  Cost train:  2510.749746758975  Cost test:  2584.9492103750295
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Iteration :  2013  Cost train:  2441.3855656153273  Cost test:  2514.6705588064333
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Iteration :  2015  Cost train:  2441.3606716106965  Cost test:  2514.649507700673
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Iteration :  2018  Cost train:  2441.3233565871483  Cost test:  2514.61795858301
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Iteration :  2020  Cost train:  2441.298497199001  Cost test:  2514.596944159937
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Iteration :  2843  Cost train:  2432.0852052930777  Cost test:  2506.975853796488
Iteration :  2844  Cost train:  2432.0751036065326  Cost test:  2506.9676493054335
Iteration :  2845  Cost train:  2432.065004308519  Cost test:  2506.9594470328448
Iteration :  2846  Cost train:  2432.0549073982434  Cost test:  2506.9512469777505
Iteration :  2847  Cost train:  2432.0448128749135  Cost test:  2506.943049139179
Iteration :  2848  Cost train:  2432.0347207377367  Cost test:  2506.93485351616
Iteration :  2849  Cost train:  2432.024630985922  Cost test:  2506.9266601077234
Iteration :  2850  Cost train:  2432.0145436186776  Cost test:  2506.9184689129006
Iteration :  2851  Cost train:  2432.0044586352124  Cost test:  2506.9102799307234
Iteration :  2852  Cost train:  2431.9943760347373  Cost test:  2506.9020931602263
Iteration :  2853  Cost train:  2431.9842958164622  Cost test:  2506.8939086004416
Iteration :  2854  Cost train:  2431.974217979597  Cost test:  2506.885726250404
Iteration :  2855  Cost train:  2431.964142523354  Cost test:  2506.87754610915
Iteration :  2856  Cost train:  2431.9540694469447  Cost test:  2506.869368175716
Iteration :  2857  Cost train:  2431.943998749581  Cost test:  2506.861192449139
Iteration :  2858  Cost train:  2431.933930430477  Cost test:  2506.853018928457
Iteration :  2859  Cost train:  2431.9238644888437  Cost test:  2506.84484761271
Iteration :  2860  Cost train:  2431.9138009238973  Cost test:  2506.836678500937
Iteration :  2861  Cost train:  2431.903739734851  Cost test:  2506.82851159218
Iteration :  2862  Cost train:  2431.8936809209195  Cost test:  2506.8203468854795
Iteration :  2863  Cost train:  2431.8836244813183  Cost test:  2506.8121843798785
Iteration :  2864  Cost train:  2431.8735704152623  Cost test:  2506.804024074421
Iteration :  2865  Cost train:  2431.863518721969  Cost test:  2506.795865968151
Iteration :  2866  Cost train:  2431.8534694006544  Cost test:  2506.7877100601127
Iteration :  2867  Cost train:  2431.843422450536  Cost test:  2506.7795563493532
Iteration :  2868  Cost train:  2431.8333778708316  Cost test:  2506.7714048349194
Iteration :  2869  Cost train:  2431.8233356607593  Cost test:  2506.7632555158575
Iteration :  2870  Cost train:  2431.8132958195374  Cost test:  2506.7551083912185
Iteration :  2871  Cost train:  2431.803258346386  Cost test:  2506.7469634600498
Iteration :  2872  Cost train:  2431.7932232405233  Cost test:  2506.738820721402
Iteration :  2873  Cost train:  2431.783190501171  Cost test:  2506.730680174327
Iteration :  2874  Cost train:  2431.7731601275486  Cost test:  2506.7225418178764
Iteration :  2875  Cost train:  2431.763132118878  Cost test:  2506.7144056511024
Iteration :  2876  Cost train:  2431.75310647438  Cost test:  2506.706271673059
Iteration :  2877  Cost train:  2431.743083193277  Cost test:  2506.6981398828007
Iteration :  2878  Cost train:  2431.733062274792  Cost test:  2506.690010279383
Iteration :  2879  Cost train:  2431.7230437181465  Cost test:  2506.6818828618616
Iteration :  2880  Cost train:  2431.7130275225663  Cost test:  2506.6737576292935
Iteration :  2881  Cost train:  2431.703013687273  Cost test:  2506.6656345807364
Iteration :  2882  Cost train:  2431.6930022114934  Cost test:  2506.6575137152495
Iteration :  2883  Cost train:  2431.68299309445  Cost test:  2506.649395031892
Iteration :  2884  Cost train:  2431.6729863353703  Cost test:  2506.6412785297234
Iteration :  2885  Cost train:  2431.6629819334785  Cost test:  2506.6331642078057
Iteration :  2886  Cost train:  2431.652979888001  Cost test:  2506.625052065201
Iteration :  2887  Cost train:  2431.6429801981662  Cost test:  2506.6169421009713
Convergence Achieved at  2887.0  iteration
Cost Minima Found :  2431.6429801981662
Betas : 
X0           121.900462
Windspeed     54.107620
RH_out      -340.961600
RH_6         -81.792445
RH_8        -102.837000
RH_1          97.984207
T1            15.644724
T3            27.950460
RH_3          60.718031
T5            -3.615201
T_out         75.325509
dtype: float64

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_pick['Iteration'],
                            y=graph_pick['Cost_train'],
                            name='Train_pick',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_pick['Iteration'],
                            y=graph_pick['Cost_test'],
                            name='Test_pick',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

Logistic Regression with Initial input parameters¶

data= pd.read_csv("energydata_complete.csv")
data.drop(['date','lights','T9','T6','Visibility','rv1','rv2'],axis=1,inplace=True)

x=data.iloc[:,1:]
y=data.iloc[:,0]

from sklearn.preprocessing import StandardScaler

scaler = StandardScaler()
x_scaled = scaler.fit_transform(x)
x_scaled

array([[-1.11864475,  1.84382063, -0.52041138, ...,  0.82208042,
         1.20769354,  0.3669753 ],
       [-1.11864475,  1.61680671, -0.52041138, ...,  0.82208042,
         1.07170342,  0.34313479],
       [-1.11864475,  1.51795932, -0.52041138, ...,  0.82208042,
         0.93571331,  0.31929428],
       ...,
       [ 2.37445166,  1.59251371,  2.41110339, ..., -1.57154154,
        -0.15220764,  2.26626907],
       [ 2.37445166,  1.6913611 ,  2.31325594, ..., -1.54917124,
        -0.08421258,  2.25832223],
       [ 2.37445166,  1.5933514 ,  2.24498422, ..., -1.52680094,
        -0.01621752,  2.2503754 ]])

x_scaled=np.concatenate((np.ones((x_scaled.shape[0], 1)), x_scaled), axis=1)

y=y.apply(lambda x: 1 if x>60 else 0)
y=np.array(y)

x_train, x_test, y_train, y_test = train_test_split(x_scaled, y, test_size=0.3,random_state=85)

#x_train=np.array(x_train)
#x_test=np.array(x_test)
#y_train=np.array(y_train)
#y_test=np.array(y_test)

x_test

array([[ 1.        , -0.7616557 , -0.67846317, ...,  1.090524  ,
        -0.83215823, -0.55088425],
       [ 1.        , -1.25770444, -0.77814824, ..., -0.00562063,
        -0.01621752, -1.47669063],
       [ 1.        ,  1.06064891, -0.96997919, ...,  0.59837743,
        -0.42418787,  0.34313479],
       ...,
       [ 1.        ,  1.06064891, -0.62066257, ..., -1.41494944,
        -0.96814834,  0.16035756],
       [ 1.        ,  0.81781333,  0.57974682, ..., -1.45969004,
        -0.42418787,  0.74842342],
       [ 1.        ,  1.17065135,  1.85973674, ..., -0.18458302,
        -0.83215823,  1.34443611]])

def y_hat_sigmoid(x,betas):
    z = np.dot(x, betas)
    return 1 / (1 + np.exp(-z))

def cost_sigmoid(x,y,betas):
    y_hat = y_hat_sigmoid(x,betas)
    return (-y * np.log(y_hat) - (1 - y) * np.log(1 - y_hat)).mean()

def batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,alpha,max_runs):
    betas=np.zeros(x_train.shape[1])
    initial_beta=betas
    
    graph=np.empty([0,5])
    
    for i in range(max_runs):
            ## Training Cost Calculation
            cost_train=cost_sigmoid(x_train,y_train,betas)
            
            ## Test Cost Calculation
            cost_test=cost_sigmoid(x_test,y_test,betas)
            
            ## Accuracy test
            y_test_pred= y_hat_sigmoid(x_test, betas) >=0.5
            Acc=(y_test_pred == y_test).mean()
                                  
            ## Update Rule
            y_hat=y_hat_sigmoid(x_train,betas)
            gradient = np.dot(x_train.T, (y_hat - y_train)) / y_train.size
            betas -= alpha * gradient
                        
            if i%1000 ==0:
                print("Iteration : ",i," Cost train: ",cost_train)
                #### Appending data graph variable
                graph=np.vstack([graph,[i,alpha,cost_test,cost_train,Acc]])
    return initial_beta,betas,graph

initial_params,params,graph=batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,0.01,300000)

Iteration :  0  Cost train:  0.6931471805599453
Iteration :  1000  Cost train:  0.5754121195612154
Iteration :  2000  Cost train:  0.5562130094304001
Iteration :  3000  Cost train:  0.5480208386737477
Iteration :  4000  Cost train:  0.5436845624290622
Iteration :  5000  Cost train:  0.5410109657027355
Iteration :  6000  Cost train:  0.5391621631580232
Iteration :  7000  Cost train:  0.537773445871137
Iteration :  8000  Cost train:  0.5366692204402282
Iteration :  9000  Cost train:  0.5357570839878492
Iteration :  10000  Cost train:  0.5349841644579463
Iteration :  11000  Cost train:  0.5343177132974286
Iteration :  12000  Cost train:  0.5337359271965817
Iteration :  13000  Cost train:  0.5332233613981848
Iteration :  14000  Cost train:  0.5327685134314385
Iteration :  15000  Cost train:  0.5323624807791085
Iteration :  16000  Cost train:  0.5319981733059294
Iteration :  17000  Cost train:  0.5316698248313447
Iteration :  18000  Cost train:  0.5313726733546555
Iteration :  19000  Cost train:  0.5311027409165684
Iteration :  20000  Cost train:  0.5308566752448306
Iteration :  21000  Cost train:  0.5306316316096306
Iteration :  22000  Cost train:  0.5304251820772125
Iteration :  23000  Cost train:  0.5302352442188494
Iteration :  24000  Cost train:  0.5300600241309265
Iteration :  25000  Cost train:  0.529897970290687
Iteration :  26000  Cost train:  0.5297477358067607
Iteration :  27000  Cost train:  0.5296081472910674
Iteration :  28000  Cost train:  0.5294781790264811
Iteration :  29000  Cost train:  0.5293569314162312
Iteration :  30000  Cost train:  0.5292436129249674
Iteration :  31000  Cost train:  0.5291375248869222
Iteration :  32000  Cost train:  0.5290380486817453
Iteration :  33000  Cost train:  0.5289446348749788
Iteration :  34000  Cost train:  0.5288567939955213
Iteration :  35000  Cost train:  0.5287740886820582
Iteration :  36000  Cost train:  0.5286961269780812
Iteration :  37000  Cost train:  0.5286225565934797
Iteration :  38000  Cost train:  0.5285530599817789
Iteration :  39000  Cost train:  0.5284873501074315
Iteration :  40000  Cost train:  0.528425166798322
Iteration :  41000  Cost train:  0.528366273595704
Iteration :  42000  Cost train:  0.5283104550278763
Iteration :  43000  Cost train:  0.5282575142455728
Iteration :  44000  Cost train:  0.5282072709667328
Iteration :  45000  Cost train:  0.5281595596864062
Iteration :  46000  Cost train:  0.5281142281142952
Iteration :  47000  Cost train:  0.528071135808097
Iteration :  48000  Cost train:  0.5280301529755634
Iteration :  49000  Cost train:  0.527991159422194
Iteration :  50000  Cost train:  0.5279540436248545
Iteration :  51000  Cost train:  0.5279187019144695
Iteration :  52000  Cost train:  0.5278850377533494
Iteration :  53000  Cost train:  0.5278529610947663
Iteration :  54000  Cost train:  0.5278223878141375
Iteration :  55000  Cost train:  0.5277932392026563
Iteration :  56000  Cost train:  0.5277654415154801
Iteration :  57000  Cost train:  0.5277389255676607
Iteration :  58000  Cost train:  0.5277136263719348
Iteration :  59000  Cost train:  0.5276894828132778
Iteration :  60000  Cost train:  0.5276664373558059
Iteration :  61000  Cost train:  0.5276444357781969
Iteration :  62000  Cost train:  0.5276234269342986
Iteration :  63000  Cost train:  0.5276033625360276
Iteration :  64000  Cost train:  0.5275841969560331
Iteration :  65000  Cost train:  0.5275658870479236
Iteration :  66000  Cost train:  0.5275483919821272
Iteration :  67000  Cost train:  0.5275316730957026
Iteration :  68000  Cost train:  0.5275156937546204
Iteration :  69000  Cost train:  0.5275004192272197
Iteration :  70000  Cost train:  0.5274858165676961
Iteration :  71000  Cost train:  0.5274718545086182
Iteration :  72000  Cost train:  0.5274585033615852
Iteration :  73000  Cost train:  0.5274457349252407
Iteration :  74000  Cost train:  0.5274335223999514
Iteration :  75000  Cost train:  0.5274218403085339
Iteration :  76000  Cost train:  0.5274106644224815
Iteration :  77000  Cost train:  0.5273999716932076
Iteration :  78000  Cost train:  0.5273897401878687
Iteration :  79000  Cost train:  0.5273799490293808
Iteration :  80000  Cost train:  0.5273705783402811
Iteration :  81000  Cost train:  0.5273616091901238
Iteration :  82000  Cost train:  0.5273530235461291
Iteration :  83000  Cost train:  0.5273448042268349
Iteration :  84000  Cost train:  0.5273369348585206
Iteration :  85000  Cost train:  0.5273293998342005
Iteration :  86000  Cost train:  0.5273221842749957
Iteration :  87000  Cost train:  0.5273152739937199
Iteration :  88000  Cost train:  0.5273086554605204
Iteration :  89000  Cost train:  0.5273023157704361
Iteration :  90000  Cost train:  0.5272962426127421
Iteration :  91000  Cost train:  0.5272904242419661
Iteration :  92000  Cost train:  0.5272848494504642
Iteration :  93000  Cost train:  0.5272795075424616
Iteration :  94000  Cost train:  0.5272743883094624
Iteration :  95000  Cost train:  0.5272694820069475
Iteration :  96000  Cost train:  0.5272647793322817
Iteration :  97000  Cost train:  0.5272602714037563
Iteration :  98000  Cost train:  0.5272559497407037
Iteration :  99000  Cost train:  0.5272518062446182
Iteration :  100000  Cost train:  0.5272478331812288
Iteration :  101000  Cost train:  0.5272440231634679
Iteration :  102000  Cost train:  0.5272403691352857
Iteration :  103000  Cost train:  0.5272368643562675
Iteration :  104000  Cost train:  0.5272335023870034
Iteration :  105000  Cost train:  0.5272302770751761
Iteration :  106000  Cost train:  0.5272271825423247
Iteration :  107000  Cost train:  0.5272242131712493
Iteration :  108000  Cost train:  0.5272213635940237
Iteration :  109000  Cost train:  0.5272186286805831
Iteration :  110000  Cost train:  0.5272160035278581
Iteration :  111000  Cost train:  0.5272134834494263
Iteration :  112000  Cost train:  0.5272110639656554
Iteration :  113000  Cost train:  0.5272087407943126
Iteration :  114000  Cost train:  0.5272065098416168
Iteration :  115000  Cost train:  0.5272043671937126
Iteration :  116000  Cost train:  0.527202309108542
Iteration :  117000  Cost train:  0.527200332008099
Iteration :  118000  Cost train:  0.5271984324710421
Iteration :  119000  Cost train:  0.5271966072256534
Iteration :  120000  Cost train:  0.5271948531431221
Iteration :  121000  Cost train:  0.5271931672311405
Iteration :  122000  Cost train:  0.5271915466277947
Iteration :  123000  Cost train:  0.5271899885957372
Iteration :  124000  Cost train:  0.5271884905166278
Iteration :  125000  Cost train:  0.5271870498858287
Iteration :  126000  Cost train:  0.5271856643073437
Iteration :  127000  Cost train:  0.527184331488988
Iteration :  128000  Cost train:  0.5271830492377787
Iteration :  129000  Cost train:  0.5271818154555349
Iteration :  130000  Cost train:  0.5271806281346787
Iteration :  131000  Cost train:  0.5271794853542261
Iteration :  132000  Cost train:  0.5271783852759598
Iteration :  133000  Cost train:  0.5271773261407754
Iteration :  134000  Cost train:  0.5271763062651924
Iteration :  135000  Cost train:  0.5271753240380231
Iteration :  136000  Cost train:  0.5271743779171915
Iteration :  137000  Cost train:  0.5271734664266942
Iteration :  138000  Cost train:  0.5271725881537002
Iteration :  139000  Cost train:  0.5271717417457781
Iteration :  140000  Cost train:  0.5271709259082503
Iteration :  141000  Cost train:  0.5271701394016636
Iteration :  142000  Cost train:  0.5271693810393733
Iteration :  143000  Cost train:  0.5271686496852359
Iteration :  144000  Cost train:  0.5271679442514048
Iteration :  145000  Cost train:  0.5271672636962222
Iteration :  146000  Cost train:  0.5271666070222081
Iteration :  147000  Cost train:  0.5271659732741355
Iteration :  148000  Cost train:  0.5271653615371932
Iteration :  149000  Cost train:  0.5271647709352291
Iteration :  150000  Cost train:  0.5271642006290719
Iteration :  151000  Cost train:  0.5271636498149266
Iteration :  152000  Cost train:  0.5271631177228411
Iteration :  153000  Cost train:  0.5271626036152409
Iteration :  154000  Cost train:  0.527162106785528
Iteration :  155000  Cost train:  0.5271616265567419
Iteration :  156000  Cost train:  0.5271611622802794
Iteration :  157000  Cost train:  0.5271607133346712
Iteration :  158000  Cost train:  0.527160279124411
Iteration :  159000  Cost train:  0.5271598590788383
Iteration :  160000  Cost train:  0.5271594526510679
Iteration :  161000  Cost train:  0.527159059316968
Iteration :  162000  Cost train:  0.5271586785741817
Iteration :  163000  Cost train:  0.5271583099411936
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Iteration :  165000  Cost train:  0.5271576071774251
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Iteration :  170000  Cost train:  0.5271560321182697
Iteration :  171000  Cost train:  0.5271557452522213
Iteration :  172000  Cost train:  0.5271554669647744
Iteration :  173000  Cost train:  0.5271551969395595
Iteration :  174000  Cost train:  0.5271549348731007
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Iteration :  181000  Cost train:  0.5271533002263864
Iteration :  182000  Cost train:  0.527153092281858
Iteration :  183000  Cost train:  0.5271528900620219
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Iteration :  191000  Cost train:  0.527151455865339
Iteration :  192000  Cost train:  0.5271512970143106
Iteration :  193000  Cost train:  0.5271511422004682
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Iteration :  202000  Cost train:  0.5271499099933373
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Iteration :  221000  Cost train:  0.5271480177293384
Iteration :  222000  Cost train:  0.5271479378942318
Iteration :  223000  Cost train:  0.5271478596609239
Iteration :  224000  Cost train:  0.5271477829860609
Iteration :  225000  Cost train:  0.5271477078277922
Iteration :  226000  Cost train:  0.5271476341457121
Iteration :  227000  Cost train:  0.5271475619008016
Iteration :  228000  Cost train:  0.527147491055375
Iteration :  229000  Cost train:  0.5271474215730264
Iteration :  230000  Cost train:  0.5271473534185808
Iteration :  231000  Cost train:  0.5271472865580449
Iteration :  232000  Cost train:  0.5271472209585615
Iteration :  233000  Cost train:  0.5271471565883655
Iteration :  234000  Cost train:  0.5271470934167416
Iteration :  235000  Cost train:  0.527147031413983
Iteration :  236000  Cost train:  0.5271469705513533
Iteration :  237000  Cost train:  0.527146910801049
Iteration :  238000  Cost train:  0.5271468521361637
Iteration :  239000  Cost train:  0.5271467945306537
Iteration :  240000  Cost train:  0.5271467379593052
Iteration :  241000  Cost train:  0.5271466823977028
Iteration :  242000  Cost train:  0.5271466278221993
Iteration :  243000  Cost train:  0.5271465742098868
Iteration :  244000  Cost train:  0.5271465215385686
Iteration :  245000  Cost train:  0.5271464697867329
Iteration :  246000  Cost train:  0.5271464189335268
Iteration :  247000  Cost train:  0.5271463689587322
Iteration :  248000  Cost train:  0.5271463198427423
Iteration :  249000  Cost train:  0.5271462715665381
Iteration :  250000  Cost train:  0.5271462241116682
Iteration :  251000  Cost train:  0.5271461774602269
Iteration :  252000  Cost train:  0.5271461315948344
Iteration :  253000  Cost train:  0.5271460864986183
Iteration :  254000  Cost train:  0.5271460421551943
Iteration :  255000  Cost train:  0.5271459985486497
Iteration :  256000  Cost train:  0.5271459556635251
Iteration :  257000  Cost train:  0.5271459134847993
Iteration :  258000  Cost train:  0.5271458719978738
Iteration :  259000  Cost train:  0.5271458311885563
Iteration :  260000  Cost train:  0.5271457910430478
Iteration :  261000  Cost train:  0.5271457515479289
Iteration :  262000  Cost train:  0.5271457126901452
Iteration :  263000  Cost train:  0.5271456744569959
Iteration :  264000  Cost train:  0.5271456368361208
Iteration :  265000  Cost train:  0.5271455998154889
Iteration :  266000  Cost train:  0.527145563383387
Iteration :  267000  Cost train:  0.5271455275284092
Iteration :  268000  Cost train:  0.5271454922394454
Iteration :  269000  Cost train:  0.5271454575056729
Iteration :  270000  Cost train:  0.5271454233165455
Iteration :  271000  Cost train:  0.5271453896617849
Iteration :  272000  Cost train:  0.5271453565313715
Iteration :  273000  Cost train:  0.5271453239155361
Iteration :  274000  Cost train:  0.5271452918047514
Iteration :  275000  Cost train:  0.5271452601897247
Iteration :  276000  Cost train:  0.5271452290613895
Iteration :  277000  Cost train:  0.5271451984108984
Iteration :  278000  Cost train:  0.5271451682296169
Iteration :  279000  Cost train:  0.5271451385091154
Iteration :  280000  Cost train:  0.5271451092411635
Iteration :  281000  Cost train:  0.5271450804177241
Iteration :  282000  Cost train:  0.527145052030946
Iteration :  283000  Cost train:  0.5271450240731592
Iteration :  284000  Cost train:  0.5271449965368694
Iteration :  285000  Cost train:  0.527144969414752
Iteration :  286000  Cost train:  0.5271449426996471
Iteration :  287000  Cost train:  0.5271449163845551
Iteration :  288000  Cost train:  0.5271448904626311
Iteration :  289000  Cost train:  0.5271448649271806
Iteration :  290000  Cost train:  0.5271448397716554
Iteration :  291000  Cost train:  0.5271448149896487
Iteration :  292000  Cost train:  0.5271447905748915
Iteration :  293000  Cost train:  0.5271447665212483
Iteration :  294000  Cost train:  0.5271447428227131
Iteration :  295000  Cost train:  0.5271447194734066
Iteration :  296000  Cost train:  0.5271446964675712
Iteration :  297000  Cost train:  0.5271446737995689
Iteration :  298000  Cost train:  0.5271446514638773
Iteration :  299000  Cost train:  0.5271446294550864

graph_df=pd.DataFrame(graph,columns=['Iteration','Alpha','Cost_test','Cost_train','Accuracy'])

graph_df

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_df['Iteration'],
                            y=graph_df['Cost_train'],
                            name='Train',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_df['Iteration'],
                            y=graph_df['Cost_test'],
                            name='Test',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_df['Iteration'],
                            y=graph_df['Accuracy'],
                            name='Accuracy',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_df['Iteration'],
                            y=graph_df['Cost_test'],
                            name='Cost',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost/Accuracy Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost/Accuracy'))
fig.show()

params

array([-0.21147109,  0.50361482,  2.31023023, -0.91327811, -1.59587164,
        0.45991356, -0.12302401,  0.0096081 ,  0.56853706, -0.18931435,
        0.27639366,  0.3267584 , -1.20526643,  0.17878782,  1.1935394 ,
       -1.38680504, -0.65079985,  0.39686564,  0.03414468, -0.04585747,
        0.20285067, -0.04318555])

pd.Series(params,index=x.columns.insert(0,'X0'))

X0            -0.211471
T1             0.503615
RH_1           2.310230
T2            -0.913278
RH_2          -1.595872
T3             0.459914
RH_3          -0.123024
T4             0.009608
RH_4           0.568537
T5            -0.189314
RH_5           0.276394
RH_6           0.326758
T7            -1.205266
RH_7           0.178788
T8             1.193539
RH_8          -1.386805
RH_9          -0.650800
T_out          0.396866
Press_mm_hg    0.034145
RH_out        -0.045857
Windspeed      0.202851
Tdewpoint     -0.043186
dtype: float64

x=[0.01,0.05,0.08,0.1,0.5,0.8]
logistic_param=np.empty([0,5])
for i in x:
    initial_params_1,params_1,graph_1=batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,i,300000)
    logistic_param=np.vstack([logistic_param,graph_1])

Iteration :  0  Cost train:  0.6931471805599453
Iteration :  1000  Cost train:  0.5754121195612154
Iteration :  2000  Cost train:  0.5562130094304001
Iteration :  3000  Cost train:  0.5480208386737477
Iteration :  4000  Cost train:  0.5436845624290622
Iteration :  5000  Cost train:  0.5410109657027355
Iteration :  6000  Cost train:  0.5391621631580232
Iteration :  7000  Cost train:  0.537773445871137
Iteration :  8000  Cost train:  0.5366692204402282
Iteration :  9000  Cost train:  0.5357570839878492
Iteration :  10000  Cost train:  0.5349841644579463
Iteration :  11000  Cost train:  0.5343177132974286
Iteration :  12000  Cost train:  0.5337359271965817
Iteration :  13000  Cost train:  0.5332233613981848
Iteration :  14000  Cost train:  0.5327685134314385
Iteration :  15000  Cost train:  0.5323624807791085
Iteration :  16000  Cost train:  0.5319981733059294
Iteration :  17000  Cost train:  0.5316698248313447
Iteration :  18000  Cost train:  0.5313726733546555
Iteration :  19000  Cost train:  0.5311027409165684
Iteration :  20000  Cost train:  0.5308566752448306
Iteration :  21000  Cost train:  0.5306316316096306
Iteration :  22000  Cost train:  0.5304251820772125
Iteration :  23000  Cost train:  0.5302352442188494
Iteration :  24000  Cost train:  0.5300600241309265
Iteration :  25000  Cost train:  0.529897970290687
Iteration :  26000  Cost train:  0.5297477358067607
Iteration :  27000  Cost train:  0.5296081472910674
Iteration :  28000  Cost train:  0.5294781790264811
Iteration :  29000  Cost train:  0.5293569314162312
Iteration :  30000  Cost train:  0.5292436129249674
Iteration :  31000  Cost train:  0.5291375248869222
Iteration :  32000  Cost train:  0.5290380486817453
Iteration :  33000  Cost train:  0.5289446348749788
Iteration :  34000  Cost train:  0.5288567939955213
Iteration :  35000  Cost train:  0.5287740886820582
Iteration :  36000  Cost train:  0.5286961269780812
Iteration :  37000  Cost train:  0.5286225565934797
Iteration :  38000  Cost train:  0.5285530599817789
Iteration :  39000  Cost train:  0.5284873501074315
Iteration :  40000  Cost train:  0.528425166798322
Iteration :  41000  Cost train:  0.528366273595704
Iteration :  42000  Cost train:  0.5283104550278763
Iteration :  43000  Cost train:  0.5282575142455728
Iteration :  44000  Cost train:  0.5282072709667328
Iteration :  45000  Cost train:  0.5281595596864062
Iteration :  46000  Cost train:  0.5281142281142952
Iteration :  47000  Cost train:  0.528071135808097
Iteration :  48000  Cost train:  0.5280301529755634
Iteration :  49000  Cost train:  0.527991159422194
Iteration :  50000  Cost train:  0.5279540436248545
Iteration :  51000  Cost train:  0.5279187019144695
Iteration :  52000  Cost train:  0.5278850377533494
Iteration :  53000  Cost train:  0.5278529610947663
Iteration :  54000  Cost train:  0.5278223878141375
Iteration :  55000  Cost train:  0.5277932392026563
Iteration :  56000  Cost train:  0.5277654415154801
Iteration :  57000  Cost train:  0.5277389255676607
Iteration :  58000  Cost train:  0.5277136263719348
Iteration :  59000  Cost train:  0.5276894828132778
Iteration :  60000  Cost train:  0.5276664373558059
Iteration :  61000  Cost train:  0.5276444357781969
Iteration :  62000  Cost train:  0.5276234269342986
Iteration :  63000  Cost train:  0.5276033625360276
Iteration :  64000  Cost train:  0.5275841969560331
Iteration :  65000  Cost train:  0.5275658870479236
Iteration :  66000  Cost train:  0.5275483919821272
Iteration :  67000  Cost train:  0.5275316730957026
Iteration :  68000  Cost train:  0.5275156937546204
Iteration :  69000  Cost train:  0.5275004192272197
Iteration :  70000  Cost train:  0.5274858165676961
Iteration :  71000  Cost train:  0.5274718545086182
Iteration :  72000  Cost train:  0.5274585033615852
Iteration :  73000  Cost train:  0.5274457349252407
Iteration :  74000  Cost train:  0.5274335223999514
Iteration :  75000  Cost train:  0.5274218403085339
Iteration :  76000  Cost train:  0.5274106644224815
Iteration :  77000  Cost train:  0.5273999716932076
Iteration :  78000  Cost train:  0.5273897401878687
Iteration :  79000  Cost train:  0.5273799490293808
Iteration :  80000  Cost train:  0.5273705783402811
Iteration :  81000  Cost train:  0.5273616091901238
Iteration :  82000  Cost train:  0.5273530235461291
Iteration :  83000  Cost train:  0.5273448042268349
Iteration :  84000  Cost train:  0.5273369348585206
Iteration :  85000  Cost train:  0.5273293998342005
Iteration :  86000  Cost train:  0.5273221842749957
Iteration :  87000  Cost train:  0.5273152739937199
Iteration :  88000  Cost train:  0.5273086554605204
Iteration :  89000  Cost train:  0.5273023157704361
Iteration :  90000  Cost train:  0.5272962426127421
Iteration :  91000  Cost train:  0.5272904242419661
Iteration :  92000  Cost train:  0.5272848494504642
Iteration :  93000  Cost train:  0.5272795075424616
Iteration :  94000  Cost train:  0.5272743883094624
Iteration :  95000  Cost train:  0.5272694820069475
Iteration :  96000  Cost train:  0.5272647793322817
Iteration :  97000  Cost train:  0.5272602714037563
Iteration :  98000  Cost train:  0.5272559497407037
Iteration :  99000  Cost train:  0.5272518062446182
Iteration :  100000  Cost train:  0.5272478331812288
Iteration :  101000  Cost train:  0.5272440231634679
Iteration :  102000  Cost train:  0.5272403691352857
Iteration :  103000  Cost train:  0.5272368643562675
Iteration :  104000  Cost train:  0.5272335023870034
Iteration :  105000  Cost train:  0.5272302770751761
Iteration :  106000  Cost train:  0.5272271825423247
Iteration :  107000  Cost train:  0.5272242131712493
Iteration :  108000  Cost train:  0.5272213635940237
Iteration :  109000  Cost train:  0.5272186286805831
Iteration :  110000  Cost train:  0.5272160035278581
Iteration :  111000  Cost train:  0.5272134834494263
Iteration :  112000  Cost train:  0.5272110639656554
Iteration :  113000  Cost train:  0.5272087407943126
Iteration :  114000  Cost train:  0.5272065098416168
Iteration :  115000  Cost train:  0.5272043671937126
Iteration :  116000  Cost train:  0.527202309108542
Iteration :  117000  Cost train:  0.527200332008099
Iteration :  118000  Cost train:  0.5271984324710421
Iteration :  119000  Cost train:  0.5271966072256534
Iteration :  120000  Cost train:  0.5271948531431221
Iteration :  121000  Cost train:  0.5271931672311405
Iteration :  122000  Cost train:  0.5271915466277947
Iteration :  123000  Cost train:  0.5271899885957372
Iteration :  124000  Cost train:  0.5271884905166278
Iteration :  125000  Cost train:  0.5271870498858287
Iteration :  126000  Cost train:  0.5271856643073437
Iteration :  127000  Cost train:  0.527184331488988
Iteration :  128000  Cost train:  0.5271830492377787
Iteration :  129000  Cost train:  0.5271818154555349
Iteration :  130000  Cost train:  0.5271806281346787
Iteration :  131000  Cost train:  0.5271794853542261
Iteration :  132000  Cost train:  0.5271783852759598
Iteration :  133000  Cost train:  0.5271773261407754
Iteration :  134000  Cost train:  0.5271763062651924
Iteration :  135000  Cost train:  0.5271753240380231
Iteration :  136000  Cost train:  0.5271743779171915
Iteration :  137000  Cost train:  0.5271734664266942
Iteration :  138000  Cost train:  0.5271725881537002
Iteration :  139000  Cost train:  0.5271717417457781
Iteration :  140000  Cost train:  0.5271709259082503
Iteration :  141000  Cost train:  0.5271701394016636
Iteration :  142000  Cost train:  0.5271693810393733
Iteration :  143000  Cost train:  0.5271686496852359
Iteration :  144000  Cost train:  0.5271679442514048
Iteration :  145000  Cost train:  0.5271672636962222
Iteration :  146000  Cost train:  0.5271666070222081
Iteration :  147000  Cost train:  0.5271659732741355
Iteration :  148000  Cost train:  0.5271653615371932
Iteration :  149000  Cost train:  0.5271647709352291
Iteration :  150000  Cost train:  0.5271642006290719
Iteration :  151000  Cost train:  0.5271636498149266
Iteration :  152000  Cost train:  0.5271631177228411
Iteration :  153000  Cost train:  0.5271626036152409
Iteration :  154000  Cost train:  0.527162106785528
Iteration :  155000  Cost train:  0.5271616265567419
Iteration :  156000  Cost train:  0.5271611622802794
Iteration :  157000  Cost train:  0.5271607133346712
Iteration :  158000  Cost train:  0.527160279124411
Iteration :  159000  Cost train:  0.5271598590788383
Iteration :  160000  Cost train:  0.5271594526510679
Iteration :  161000  Cost train:  0.527159059316968
Iteration :  162000  Cost train:  0.5271586785741817
Iteration :  163000  Cost train:  0.5271583099411936
Iteration :  164000  Cost train:  0.5271579529564338
Iteration :  165000  Cost train:  0.5271576071774251
Iteration :  166000  Cost train:  0.5271572721799634
Iteration :  167000  Cost train:  0.5271569475573378
Iteration :  168000  Cost train:  0.5271566329195811
Iteration :  169000  Cost train:  0.5271563278927559
Iteration :  170000  Cost train:  0.5271560321182697
Iteration :  171000  Cost train:  0.5271557452522213
Iteration :  172000  Cost train:  0.5271554669647744
Iteration :  173000  Cost train:  0.5271551969395595
Iteration :  174000  Cost train:  0.5271549348731007
Iteration :  175000  Cost train:  0.5271546804742687
Iteration :  176000  Cost train:  0.5271544334637559
Iteration :  177000  Cost train:  0.5271541935735754
Iteration :  178000  Cost train:  0.5271539605465819
Iteration :  179000  Cost train:  0.5271537341360122
Iteration :  180000  Cost train:  0.5271535141050459
Iteration :  181000  Cost train:  0.5271533002263864
Iteration :  182000  Cost train:  0.527153092281858
Iteration :  183000  Cost train:  0.5271528900620219
Iteration :  184000  Cost train:  0.5271526933658077
Iteration :  185000  Cost train:  0.5271525020001616
Iteration :  186000  Cost train:  0.5271523157797097
Iteration :  187000  Cost train:  0.5271521345264344
Iteration :  188000  Cost train:  0.5271519580693672
Iteration :  189000  Cost train:  0.5271517862442924
Iteration :  190000  Cost train:  0.5271516188934648
Iteration :  191000  Cost train:  0.527151455865339
Iteration :  192000  Cost train:  0.5271512970143106
Iteration :  193000  Cost train:  0.5271511422004682
Iteration :  194000  Cost train:  0.5271509912893562
Iteration :  195000  Cost train:  0.5271508441517481
Iteration :  196000  Cost train:  0.5271507006634284
Iteration :  197000  Cost train:  0.5271505607049852
Iteration :  198000  Cost train:  0.5271504241616108
Iteration :  199000  Cost train:  0.5271502909229109
Iteration :  200000  Cost train:  0.5271501608827219
Iteration :  201000  Cost train:  0.5271500339389369
Iteration :  202000  Cost train:  0.5271499099933373
Iteration :  203000  Cost train:  0.5271497889514335
Iteration :  204000  Cost train:  0.5271496707223107
Iteration :  205000  Cost train:  0.527149555218483
Iteration :  206000  Cost train:  0.5271494423557517
Iteration :  207000  Cost train:  0.5271493320530718
Iteration :  208000  Cost train:  0.5271492242324218
Iteration :  209000  Cost train:  0.527149118818681
Iteration :  210000  Cost train:  0.5271490157395113
Iteration :  211000  Cost train:  0.5271489149252436
Iteration :  212000  Cost train:  0.5271488163087693
Iteration :  213000  Cost train:  0.5271487198254368
Iteration :  214000  Cost train:  0.5271486254129513
Iteration :  215000  Cost train:  0.5271485330112806
Iteration :  216000  Cost train:  0.5271484425625629
Iteration :  217000  Cost train:  0.5271483540110194
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Iteration :  219000  Cost train:  0.5271481823862586
Iteration :  220000  Cost train:  0.5271480992111639
Iteration :  221000  Cost train:  0.5271480177293384
Iteration :  222000  Cost train:  0.5271479378942318
Iteration :  223000  Cost train:  0.5271478596609239
Iteration :  224000  Cost train:  0.5271477829860609
Iteration :  225000  Cost train:  0.5271477078277922
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Iteration :  230000  Cost train:  0.5271473534185808
Iteration :  231000  Cost train:  0.5271472865580449
Iteration :  232000  Cost train:  0.5271472209585615
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Iteration :  240000  Cost train:  0.5271467379593052
Iteration :  241000  Cost train:  0.5271466823977028
Iteration :  242000  Cost train:  0.5271466278221993
Iteration :  243000  Cost train:  0.5271465742098868
Iteration :  244000  Cost train:  0.5271465215385686
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Iteration :  250000  Cost train:  0.5271462241116682
Iteration :  251000  Cost train:  0.5271461774602269
Iteration :  252000  Cost train:  0.5271461315948344
Iteration :  253000  Cost train:  0.5271460864986183
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Iteration :  293000  Cost train:  0.5271430864446002
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Iteration :  297000  Cost train:  0.5271430864446002
Iteration :  298000  Cost train:  0.5271430864446002
Iteration :  299000  Cost train:  0.5271430864446002

logistic_param_1=pd.DataFrame(logistic_param,columns=['Iteration','Alpha','Cost_test','Cost_train','Accuracy'])

logistic_param_1

pd.concat([logistic_param_1.groupby('Alpha')['Cost_test'].min(),
           logistic_param_1.groupby('Alpha')['Accuracy'].max(),],axis=1)

pd.concat([logistic_param_1.groupby('Alpha')['Accuracy'].max(),
           logistic_param_1.groupby('Alpha')['Iteration'].max(),],axis=1)

import plotly.express as px
px.line(logistic_param_1, x="Iteration", y="Accuracy", color="Alpha")

initial_params_1,params_1,graph_1=batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,0.01,300000)

graph1=pd.DataFrame(graph[1:,:],columns=['Iteration','Alpha','Cost_test','Cost_train','Accuracy'])

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph1['Iteration'],
                        y=graph1['Accuracy'],
                        mode='lines'))
fig.update_layout(title='Accuracy Vs Iteration',
                 xaxis=dict(title='Iteration'),yaxis=dict(title='Accuracy'))
fig.show()

Experiment with randomly picked variables(Experiment 3)¶

x=data.iloc[:,1:]
y=data.iloc[:,0]

x_sampled=x.sample(10,axis=1,random_state=48)

x_sampled.columns

Index(['RH_1', 'RH_5', 'RH_3', 'RH_4', 'T5', 'RH_7', 'RH_out', 'RH_2', 'T7',
       'RH_6'],
      dtype='object')

scaler = StandardScaler()
x_scaled = scaler.fit_transform(x_sampled)
x_scaled

array([[ 1.84382063,  0.47116038,  1.68612997, ...,  1.07368343,
        -1.45364639,  0.95179837],
       [ 1.61680671,  0.47116038,  1.70456601, ...,  1.05709748,
        -1.45364639,  0.94559165],
       [ 1.51795932,  0.45896769,  1.74860768, ...,  1.03354953,
        -1.45364639,  0.91648425],
       ...,
       [ 1.59251371,  0.14602221,  0.752037  , ...,  0.57698247,
         2.02512574, -1.72105219],
       [ 1.6913611 ,  0.13863271,  0.62913003, ...,  0.64269443,
         2.00616785, -1.72105219],
       [ 1.5933514 ,  0.13863271,  0.58816104, ...,  0.62682808,
         2.00616785, -1.72105219]])

x_scaled=np.concatenate((np.ones((x_scaled.shape[0], 1)), x_scaled), axis=1)

y=y.apply(lambda x: 1 if x>60 else 0)
y=np.array(y)

x_train, x_test, y_train, y_test = train_test_split(x_scaled, y, test_size=0.3,random_state=85)

initial_params,params,graph=batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,0.5,300000)

Iteration :  0  Cost train:  0.6931471805599453
Iteration :  1000  Cost train:  0.5919584896464972
Iteration :  2000  Cost train:  0.5919583240533157
Iteration :  3000  Cost train:  0.5919583240497329
Iteration :  4000  Cost train:  0.5919583240497328
Iteration :  5000  Cost train:  0.5919583240497328
Iteration :  6000  Cost train:  0.5919583240497328
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Iteration :  8000  Cost train:  0.5919583240497328
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Iteration :  10000  Cost train:  0.5919583240497328
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Iteration :  100000  Cost train:  0.5919583240497328
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graph_df_1=pd.DataFrame(graph,columns=['Iteration','Alpha','Cost_test','Cost_train','Accuracy'])

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_df_1['Iteration'],
                            y=graph_df_1['Cost_train'],
                            name='Train',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_df_1['Iteration'],
                            y=graph_df_1['Cost_test'],
                            name='Test',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

Experiment 4¶

x=data.iloc[:,1:]
y=data.iloc[:,0]

x_pick=x[['Windspeed','RH_out','RH_6','RH_8','RH_1','T1','T3','RH_3','T5','T_out']]

x_pick.columns

Index(['Windspeed', 'RH_out', 'RH_6', 'RH_8', 'RH_1', 'T1', 'T3', 'RH_3', 'T5',
       'T_out'],
      dtype='object')

scaler = StandardScaler()
x_scaled = scaler.fit_transform(x_pick)
x_scaled

array([[ 1.20769354,  0.82208042,  0.95179837, ...,  1.68612997,
        -1.31490324, -0.15264674],
       [ 1.07170342,  0.82208042,  0.94559165, ...,  1.70456601,
        -1.31490324, -0.17458781],
       [ 0.93571331,  0.82208042,  0.91648425, ...,  1.74860768,
        -1.31490324, -0.19652887],
       ...,
       [-0.15220764, -1.57154154, -1.72105219, ...,  0.752037  ,
         1.97221075,  2.83133837],
       [-0.08421258, -1.54917124, -1.72105219, ...,  0.62913003,
         1.95594685,  2.80626286],
       [-0.01621752, -1.52680094, -1.72105219, ...,  0.58816104,
         1.95594685,  2.78118736]])

x_scaled=np.concatenate((np.ones((x_scaled.shape[0], 1)), x_scaled), axis=1)

y=y.apply(lambda x: 1 if x>60 else 0)
y=np.array(y)

x_train, x_test, y_train, y_test = train_test_split(x_scaled, y, test_size=0.3,random_state=85)

initial_params,params,graph=batch_gradient_descent_logistic(x_train,y_train,x_test,y_test,0.5,300000)

Iteration :  0  Cost train:  0.6931471805599453
Iteration :  1000  Cost train:  0.5896234070125407
Iteration :  2000  Cost train:  0.5896233569266309
Iteration :  3000  Cost train:  0.5896233569259435
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graph_df_2=pd.DataFrame(graph,columns=['Iteration','Alpha','Cost_test','Cost_train','Accuracy'])

graph_df_2

fig=go.Figure()
fig.add_trace(go.Scatter(x=graph_df_2['Iteration'],
                            y=graph_df_2['Cost_train'],
                            name='Train',
                             mode='lines'))
fig.add_trace(go.Scatter(x=graph_df_2['Iteration'],
                            y=graph_df_2['Cost_test'],
                            name='Test',
                             mode='lines'))
fig.update_layout(title=go.layout.Title(
                  text="Cost Vs Iteration ",xref="paper",x=0,y=0.85),
                  xaxis=dict(title='Iteration'),yaxis=dict(title='Cost'))
fig.show()

	date	Appliances	lights	T1	RH_1	T2	RH_2	T3	RH_3	T4	...	T9	RH_9	T_out	Press_mm_hg	RH_out	Windspeed	Visibility	Tdewpoint	rv1	rv2
0	2016-01-11 17:00:00	60	30	19.890000	47.596667	19.200000	44.790000	19.790000	44.730000	19.000000	...	17.033333	45.530000	6.600000	733.500000	92.000000	7.000000	63.000000	5.300000	13.275433	13.275433
1	2016-01-11 17:10:00	60	30	19.890000	46.693333	19.200000	44.722500	19.790000	44.790000	19.000000	...	17.066667	45.560000	6.483333	733.600000	92.000000	6.666667	59.166667	5.200000	18.606195	18.606195
2	2016-01-11 17:20:00	50	30	19.890000	46.300000	19.200000	44.626667	19.790000	44.933333	18.926667	...	17.000000	45.500000	6.366667	733.700000	92.000000	6.333333	55.333333	5.100000	28.642668	28.642668
3	2016-01-11 17:30:00	50	40	19.890000	46.066667	19.200000	44.590000	19.790000	45.000000	18.890000	...	17.000000	45.400000	6.250000	733.800000	92.000000	6.000000	51.500000	5.000000	45.410389	45.410389
4	2016-01-11 17:40:00	60	40	19.890000	46.333333	19.200000	44.530000	19.790000	45.000000	18.890000	...	17.000000	45.400000	6.133333	733.900000	92.000000	5.666667	47.666667	4.900000	10.084097	10.084097
5	2016-01-11 17:50:00	50	40	19.890000	46.026667	19.200000	44.500000	19.790000	44.933333	18.890000	...	17.000000	45.290000	6.016667	734.000000	92.000000	5.333333	43.833333	4.800000	44.919484	44.919484
6	2016-01-11 18:00:00	60	50	19.890000	45.766667	19.200000	44.500000	19.790000	44.900000	18.890000	...	17.000000	45.290000	5.900000	734.100000	92.000000	5.000000	40.000000	4.700000	47.233763	47.233763
7	2016-01-11 18:10:00	60	50	19.856667	45.560000	19.200000	44.500000	19.730000	44.900000	18.890000	...	17.000000	45.290000	5.916667	734.166667	91.833333	5.166667	40.000000	4.683333	33.039890	33.039890
8	2016-01-11 18:20:00	60	40	19.790000	45.597500	19.200000	44.433333	19.730000	44.790000	18.890000	...	17.000000	45.290000	5.933333	734.233333	91.666667	5.333333	40.000000	4.666667	31.455702	31.455702
9	2016-01-11 18:30:00	70	40	19.856667	46.090000	19.230000	44.400000	19.790000	44.863333	18.890000	...	17.000000	45.290000	5.950000	734.300000	91.500000	5.500000	40.000000	4.650000	3.089314	3.089314
10	2016-01-11 18:40:00	230	70	19.926667	45.863333	19.356667	44.400000	19.790000	44.900000	18.890000	...	17.000000	45.290000	5.966667	734.366667	91.333333	5.666667	40.000000	4.633333	10.298729	10.298729
11	2016-01-11 18:50:00	580	60	20.066667	46.396667	19.426667	44.400000	19.790000	44.826667	19.000000	...	16.890000	45.290000	5.983333	734.433333	91.166667	5.833333	40.000000	4.616667	8.827838	8.827838
12	2016-01-11 19:00:00	430	50	20.133333	48.000000	19.566667	44.400000	19.890000	44.900000	19.000000	...	16.963333	45.290000	6.000000	734.500000	91.000000	6.000000	40.000000	4.600000	34.351142	34.351142
13	2016-01-11 19:10:00	250	40	20.260000	52.726667	19.730000	45.100000	19.890000	45.493333	19.000000	...	16.890000	45.326667	6.000000	734.616667	90.500000	6.000000	40.000000	4.516667	19.205186	19.205186
14	2016-01-11 19:20:00	100	10	20.426667	55.893333	19.856667	45.833333	20.033333	47.526667	19.000000	...	16.890000	45.345000	6.000000	734.733333	90.000000	6.000000	40.000000	4.433333	38.492071	38.492071
15	2016-01-11 19:30:00	100	10	20.566667	53.893333	20.033333	46.756667	20.100000	48.466667	19.000000	...	16.890000	45.326667	6.000000	734.850000	89.500000	6.000000	40.000000	4.350000	24.884962	24.884962
16	2016-01-11 19:40:00	90	10	20.730000	52.660000	20.166667	47.223333	20.200000	48.530000	18.926667	...	16.890000	45.290000	6.000000	734.966667	89.000000	6.000000	40.000000	4.266667	35.880925	35.880925
17	2016-01-11 19:50:00	70	30	20.856667	53.660000	20.200000	47.056667	20.200000	48.447500	18.890000	...	16.890000	45.290000	6.000000	735.083333	88.500000	6.000000	40.000000	4.183333	49.595305	49.595305
18	2016-01-11 20:00:00	80	30	20.890000	51.193333	20.200000	46.330000	20.200000	48.193333	18.963333	...	16.890000	45.200000	6.000000	735.200000	88.000000	6.000000	40.000000	4.100000	19.001759	19.001759
19	2016-01-11 20:10:00	140	40	20.890000	49.800000	20.200000	46.026667	20.166667	47.633333	19.033333	...	16.890000	45.200000	6.000000	735.233333	87.833333	6.000000	40.000000	4.066667	38.872261	38.872261
20	2016-01-11 20:20:00	120	20	20.890000	48.433333	20.200000	45.722500	20.166667	47.300000	19.175000	...	16.890000	45.126667	6.000000	735.266667	87.666667	6.000000	40.000000	4.033333	46.735262	46.735262
21	2016-01-11 20:30:00	190	40	20.963333	47.633333	20.260000	45.530000	20.200000	47.026667	19.260000	...	16.890000	45.126667	6.000000	735.300000	87.500000	6.000000	40.000000	4.000000	10.607126	10.607126
22	2016-01-11 20:40:00	110	40	21.033333	47.063333	20.290000	45.223333	20.260000	46.826667	19.323333	...	16.890000	45.060000	6.000000	735.333333	87.333333	6.000000	40.000000	3.966667	32.583688	32.583688
23	2016-01-11 20:50:00	110	40	21.100000	46.596667	20.356667	44.963333	20.290000	46.633333	19.390000	...	16.890000	45.000000	6.000000	735.366667	87.166667	6.000000	40.000000	3.933333	6.277755	6.277755
24	2016-01-11 21:00:00	110	30	21.133333	46.060000	20.426667	44.760000	20.290000	46.433333	19.390000	...	16.890000	44.966667	6.000000	735.400000	87.000000	6.000000	40.000000	3.900000	13.361033	13.361033
25	2016-01-11 21:10:00	110	20	21.200000	45.800000	20.500000	44.760000	20.390000	46.223333	19.390000	...	16.890000	44.900000	5.933333	735.466667	87.166667	6.000000	40.000000	3.866667	19.305705	19.305705
26	2016-01-11 21:20:00	100	30	21.290000	45.900000	20.533333	45.090000	20.390000	46.090000	19.390000	...	16.890000	44.790000	5.866667	735.533333	87.333333	6.000000	40.000000	3.833333	0.669517	0.669517
27	2016-01-11 21:30:00	100	20	21.356667	45.826667	20.666667	45.163333	20.390000	46.090000	19.390000	...	16.890000	44.790000	5.800000	735.600000	87.500000	6.000000	40.000000	3.800000	19.119398	19.119398
28	2016-01-11 21:40:00	100	20	21.390000	45.690000	20.700000	45.060000	20.390000	46.090000	19.426667	...	16.890000	44.700000	5.733333	735.666667	87.666667	6.000000	40.000000	3.766667	43.484542	43.484542
29	2016-01-11 21:50:00	100	20	21.500000	45.333333	20.700000	44.933333	20.390000	46.060000	19.566667	...	16.890000	44.700000	5.666667	735.733333	87.833333	6.000000	40.000000	3.733333	17.017450	17.017450
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
19705	2016-05-27 13:10:00	280	0	25.033333	48.363333	26.528571	40.595714	28.496667	41.900000	24.500000	...	23.100000	46.500000	21.250000	756.050000	59.833333	1.166667	23.666667	13.100000	32.420348	32.420348
19706	2016-05-27 13:20:00	240	0	25.166667	48.156667	26.600000	40.940000	28.290000	41.966667	24.500000	...	23.100000	46.500000	21.400000	756.000000	59.666667	1.333333	23.333333	13.200000	49.189027	49.189027
19707	2016-05-27 13:30:00	250	0	25.323333	47.930000	26.600000	41.012857	28.200000	42.090000	24.533333	...	23.100000	46.522500	21.550000	755.950000	59.500000	1.500000	23.000000	13.300000	15.081162	15.081162
19708	2016-05-27 13:40:00	220	0	25.390000	47.656667	26.600000	41.036000	28.200000	42.030000	24.600000	...	23.100000	46.530000	21.700000	755.900000	59.333333	1.666667	22.666667	13.400000	45.226866	45.226866
19709	2016-05-27 13:50:00	230	0	25.500000	47.133333	26.600000	41.000000	28.200000	41.796667	24.600000	...	23.100000	46.530000	21.850000	755.850000	59.166667	1.833333	22.333333	13.500000	5.773431	5.773431
19710	2016-05-27 14:00:00	190	10	25.500000	47.060000	26.540000	41.000000	28.200000	41.530000	24.600000	...	23.100000	46.530000	22.000000	755.800000	59.000000	2.000000	22.000000	13.600000	41.515044	41.515044
19711	2016-05-27 14:10:00	160	0	25.600000	46.990000	26.512500	41.203750	28.200000	41.590000	24.633333	...	23.100000	46.530000	21.966667	755.800000	59.000000	2.000000	21.833333	13.550000	19.540642	19.540642
19712	2016-05-27 14:20:00	80	0	25.600000	46.730000	26.437143	41.384286	28.426667	41.430000	24.700000	...	23.100000	46.590000	21.933333	755.800000	59.000000	2.000000	21.666667	13.500000	16.977597	16.977597
19713	2016-05-27 14:30:00	60	0	25.566667	46.633333	26.370000	41.378000	28.566667	41.156667	24.700000	...	23.100000	46.626667	21.900000	755.800000	59.000000	2.000000	21.500000	13.450000	8.991420	8.991420
19714	2016-05-27 14:40:00	60	0	25.500000	46.360000	26.318571	41.264286	28.566667	40.663333	24.700000	...	23.100000	46.700000	21.866667	755.800000	59.000000	2.000000	21.333333	13.400000	40.409885	40.409885
19715	2016-05-27 14:50:00	60	0	25.500000	46.060000	26.350000	41.000000	28.426667	40.590000	24.666667	...	23.100000	46.590000	21.833333	755.800000	59.000000	2.000000	21.166667	13.350000	37.889086	37.889086
19716	2016-05-27 15:00:00	60	0	25.500000	45.933333	26.277143	41.000000	28.356667	40.560000	24.666667	...	23.100000	46.590000	21.800000	755.800000	59.000000	2.000000	21.000000	13.300000	17.123315	17.123315
19717	2016-05-27 15:10:00	70	0	25.500000	45.760000	26.200000	41.000000	28.290000	40.433333	24.700000	...	23.133333	46.590000	21.966667	755.750000	58.333333	2.000000	21.333333	13.283333	24.058432	24.058432
19718	2016-05-27 15:20:00	80	0	25.500000	45.626667	26.171429	41.000000	28.260000	40.260000	24.700000	...	23.133333	46.590000	22.133333	755.700000	57.666667	2.000000	21.666667	13.266667	9.538671	9.538671
19719	2016-05-27 15:30:00	80	0	25.500000	45.590000	26.100000	41.000000	28.200000	40.126667	24.700000	...	23.166667	46.590000	22.300000	755.650000	57.000000	2.000000	22.000000	13.250000	30.020685	30.020685
19720	2016-05-27 15:40:00	70	0	25.500000	45.522500	26.100000	41.051429	28.200000	40.200000	24.700000	...	23.100000	46.590000	22.466667	755.600000	56.333333	2.000000	22.333333	13.233333	23.851737	23.851737
19721	2016-05-27 15:50:00	100	0	25.500000	45.633333	26.080000	41.196000	28.133333	40.260000	24.700000	...	23.200000	46.590000	22.633333	755.550000	55.666667	2.000000	22.666667	13.216667	47.981309	47.981309
19722	2016-05-27 16:00:00	100	0	25.500000	45.730000	26.000000	41.428571	28.100000	40.433333	24.700000	...	23.200000	46.590000	22.800000	755.500000	55.000000	2.000000	23.000000	13.200000	18.215602	18.215602
19723	2016-05-27 16:10:00	90	0	25.500000	45.790000	26.000000	41.590000	28.100000	40.560000	24.700000	...	23.160000	46.590000	22.833333	755.450000	55.000000	2.166667	22.833333	13.233333	38.751594	38.751594
19724	2016-05-27 16:20:00	100	0	25.500000	45.933333	26.000000	41.652857	28.000000	40.700000	24.700000	...	23.200000	46.621429	22.866667	755.400000	55.000000	2.333333	22.666667	13.266667	32.306224	32.306224
19725	2016-05-27 16:30:00	220	0	25.426667	46.060000	26.000000	41.700000	28.000000	40.760000	24.700000	...	23.200000	46.700000	22.900000	755.350000	55.000000	2.500000	22.500000	13.300000	23.009520	23.009520
19726	2016-05-27 16:40:00	180	0	25.500000	46.530000	26.000000	41.725714	27.856667	40.500000	24.700000	...	23.200000	46.652857	22.933333	755.300000	55.000000	2.666667	22.333333	13.333333	25.296732	25.296732
19727	2016-05-27 16:50:00	120	0	25.500000	47.456667	26.000000	42.320000	27.663333	40.693333	24.700000	...	23.200000	46.718000	22.966667	755.250000	55.000000	2.833333	22.166667	13.366667	1.796395	1.796395
19728	2016-05-27 17:00:00	110	0	25.600000	47.193333	25.968571	42.528571	27.390000	41.030000	24.700000	...	23.200000	46.751429	23.000000	755.200000	55.000000	3.000000	22.000000	13.400000	18.248201	18.248201
19729	2016-05-27 17:10:00	90	0	25.533333	46.860000	25.978000	42.534000	27.323333	41.090000	24.700000	...	23.200000	46.745000	22.866667	755.200000	55.333333	3.166667	22.833333	13.366667	16.966162	16.966162
19730	2016-05-27 17:20:00	100	0	25.566667	46.560000	25.890000	42.025714	27.200000	41.163333	24.700000	...	23.200000	46.790000	22.733333	755.200000	55.666667	3.333333	23.666667	13.333333	43.096812	43.096812
19731	2016-05-27 17:30:00	90	0	25.500000	46.500000	25.754000	42.080000	27.133333	41.223333	24.700000	...	23.200000	46.790000	22.600000	755.200000	56.000000	3.500000	24.500000	13.300000	49.282940	49.282940
19732	2016-05-27 17:40:00	270	10	25.500000	46.596667	25.628571	42.768571	27.050000	41.690000	24.700000	...	23.200000	46.790000	22.466667	755.200000	56.333333	3.666667	25.333333	13.266667	29.199117	29.199117
19733	2016-05-27 17:50:00	420	10	25.500000	46.990000	25.414000	43.036000	26.890000	41.290000	24.700000	...	23.200000	46.817500	22.333333	755.200000	56.666667	3.833333	26.166667	13.233333	6.322784	6.322784
19734	2016-05-27 18:00:00	430	10	25.500000	46.600000	25.264286	42.971429	26.823333	41.156667	24.700000	...	23.200000	46.845000	22.200000	755.200000	57.000000	4.000000	27.000000	13.200000	34.118851	34.118851

	date	Appliances	lights	T1	RH_1	T2	RH_2	T3	RH_3	T4	...	T9	RH_9	T_out	Press_mm_hg	RH_out	Windspeed	Visibility	Tdewpoint	rv1	rv2
count	19735	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	...	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000	19735.000000
unique	19735	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
top	2016-05-02 19:40:00	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
freq	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
mean	NaN	97.694958	3.801875	21.686571	40.259739	20.341219	40.420420	22.267611	39.242500	20.855335	...	19.485828	41.552401	7.411665	755.522602	79.750418	4.039752	38.330834	3.760707	24.988033	24.988033
std	NaN	102.524891	7.935988	1.606066	3.979299	2.192974	4.069813	2.006111	3.254576	2.042884	...	2.014712	4.151497	5.317409	7.399441	14.901088	2.451221	11.794719	4.194648	14.496634	14.496634
min	NaN	10.000000	0.000000	16.790000	27.023333	16.100000	20.463333	17.200000	28.766667	15.100000	...	14.890000	29.166667	-5.000000	729.300000	24.000000	0.000000	1.000000	-6.600000	0.005322	0.005322
25%	NaN	50.000000	0.000000	20.760000	37.333333	18.790000	37.900000	20.790000	36.900000	19.530000	...	18.000000	38.500000	3.666667	750.933333	70.333333	2.000000	29.000000	0.900000	12.497889	12.497889
50%	NaN	60.000000	0.000000	21.600000	39.656667	20.000000	40.500000	22.100000	38.530000	20.666667	...	19.390000	40.900000	6.916667	756.100000	83.666667	3.666667	40.000000	3.433333	24.897653	24.897653
75%	NaN	100.000000	0.000000	22.600000	43.066667	21.500000	43.260000	23.290000	41.760000	22.100000	...	20.600000	44.338095	10.408333	760.933333	91.666667	5.500000	40.000000	6.566667	37.583769	37.583769
max	NaN	1080.000000	70.000000	26.260000	63.360000	29.856667	56.026667	29.236000	50.163333	26.200000	...	24.500000	53.326667	26.100000	772.300000	100.000000	14.000000	66.000000	15.500000	49.996530	49.996530

	Iteration	Alpha	Cost_test	Cost_train	Accuracy
0	0.0	0.01	0.693147	0.693147	0.463266
1	1000.0	0.01	0.576896	0.575412	0.720655
2	2000.0	0.01	0.560245	0.556213	0.726566
3	3000.0	0.01	0.553517	0.548021	0.728593
4	4000.0	0.01	0.550086	0.543685	0.732984
5	5000.0	0.01	0.547987	0.541011	0.734167
6	6000.0	0.01	0.546506	0.539162	0.736362
7	7000.0	0.01	0.545350	0.537773	0.737207
8	8000.0	0.01	0.544389	0.536669	0.737882
9	9000.0	0.01	0.543562	0.535757	0.738558
10	10000.0	0.01	0.542833	0.534984	0.739740
11	11000.0	0.01	0.542184	0.534318	0.739909
12	12000.0	0.01	0.541602	0.533736	0.740247
13	13000.0	0.01	0.541077	0.533223	0.740922
14	14000.0	0.01	0.540602	0.532769	0.741767
15	15000.0	0.01	0.540172	0.532362	0.743287
16	16000.0	0.01	0.539780	0.531998	0.743118
17	17000.0	0.01	0.539424	0.531670	0.742611
18	18000.0	0.01	0.539098	0.531373	0.743455
19	19000.0	0.01	0.538800	0.531103	0.743962
20	20000.0	0.01	0.538527	0.530857	0.743793
21	21000.0	0.01	0.538275	0.530632	0.743118
22	22000.0	0.01	0.538044	0.530425	0.743287
23	23000.0	0.01	0.537830	0.530235	0.743118
24	24000.0	0.01	0.537633	0.530060	0.743118
25	25000.0	0.01	0.537450	0.529898	0.742442
26	26000.0	0.01	0.537280	0.529748	0.743118
27	27000.0	0.01	0.537122	0.529608	0.743287
28	28000.0	0.01	0.536975	0.529478	0.743455
29	29000.0	0.01	0.536838	0.529357	0.743624
...	...	...	...	...	...
270	270000.0	0.01	0.534359	0.527145	0.744976
271	271000.0	0.01	0.534359	0.527145	0.744976
272	272000.0	0.01	0.534359	0.527145	0.744976
273	273000.0	0.01	0.534358	0.527145	0.744976
274	274000.0	0.01	0.534358	0.527145	0.744976
275	275000.0	0.01	0.534358	0.527145	0.744976
276	276000.0	0.01	0.534357	0.527145	0.744976
277	277000.0	0.01	0.534357	0.527145	0.744976
278	278000.0	0.01	0.534356	0.527145	0.744976
279	279000.0	0.01	0.534356	0.527145	0.744976
280	280000.0	0.01	0.534356	0.527145	0.744976
281	281000.0	0.01	0.534355	0.527145	0.744976
282	282000.0	0.01	0.534355	0.527145	0.744976
283	283000.0	0.01	0.534355	0.527145	0.744976
284	284000.0	0.01	0.534354	0.527145	0.744976
285	285000.0	0.01	0.534354	0.527145	0.744976
286	286000.0	0.01	0.534354	0.527145	0.744807
287	287000.0	0.01	0.534353	0.527145	0.744638
288	288000.0	0.01	0.534353	0.527145	0.744638
289	289000.0	0.01	0.534353	0.527145	0.744638
290	290000.0	0.01	0.534352	0.527145	0.744638
291	291000.0	0.01	0.534352	0.527145	0.744638
292	292000.0	0.01	0.534352	0.527145	0.744638
293	293000.0	0.01	0.534351	0.527145	0.744638
294	294000.0	0.01	0.534351	0.527145	0.744638
295	295000.0	0.01	0.534351	0.527145	0.744638
296	296000.0	0.01	0.534350	0.527145	0.744638
297	297000.0	0.01	0.534350	0.527145	0.744638
298	298000.0	0.01	0.534350	0.527145	0.744638
299	299000.0	0.01	0.534349	0.527145	0.744638

	Iteration	Alpha	Cost_test	Cost_train	Accuracy
0	0.0	0.01	0.693147	0.693147	0.463266
1	1000.0	0.01	0.576896	0.575412	0.720655
2	2000.0	0.01	0.560245	0.556213	0.726566
3	3000.0	0.01	0.553517	0.548021	0.728593
4	4000.0	0.01	0.550086	0.543685	0.732984
5	5000.0	0.01	0.547987	0.541011	0.734167
6	6000.0	0.01	0.546506	0.539162	0.736362
7	7000.0	0.01	0.545350	0.537773	0.737207
8	8000.0	0.01	0.544389	0.536669	0.737882
9	9000.0	0.01	0.543562	0.535757	0.738558
10	10000.0	0.01	0.542833	0.534984	0.739740
11	11000.0	0.01	0.542184	0.534318	0.739909
12	12000.0	0.01	0.541602	0.533736	0.740247
13	13000.0	0.01	0.541077	0.533223	0.740922
14	14000.0	0.01	0.540602	0.532769	0.741767
15	15000.0	0.01	0.540172	0.532362	0.743287
16	16000.0	0.01	0.539780	0.531998	0.743118
17	17000.0	0.01	0.539424	0.531670	0.742611
18	18000.0	0.01	0.539098	0.531373	0.743455
19	19000.0	0.01	0.538800	0.531103	0.743962
20	20000.0	0.01	0.538527	0.530857	0.743793
21	21000.0	0.01	0.538275	0.530632	0.743118
22	22000.0	0.01	0.538044	0.530425	0.743287
23	23000.0	0.01	0.537830	0.530235	0.743118
24	24000.0	0.01	0.537633	0.530060	0.743118
25	25000.0	0.01	0.537450	0.529898	0.742442
26	26000.0	0.01	0.537280	0.529748	0.743118
27	27000.0	0.01	0.537122	0.529608	0.743287
28	28000.0	0.01	0.536975	0.529478	0.743455
29	29000.0	0.01	0.536838	0.529357	0.743624
...	...	...	...	...	...
1770	270000.0	0.80	0.534304	0.527143	0.744131
1771	271000.0	0.80	0.534304	0.527143	0.744131
1772	272000.0	0.80	0.534304	0.527143	0.744131
1773	273000.0	0.80	0.534304	0.527143	0.744131
1774	274000.0	0.80	0.534304	0.527143	0.744131
1775	275000.0	0.80	0.534304	0.527143	0.744131
1776	276000.0	0.80	0.534304	0.527143	0.744131
1777	277000.0	0.80	0.534304	0.527143	0.744131
1778	278000.0	0.80	0.534304	0.527143	0.744131
1779	279000.0	0.80	0.534304	0.527143	0.744131
1780	280000.0	0.80	0.534304	0.527143	0.744131
1781	281000.0	0.80	0.534304	0.527143	0.744131
1782	282000.0	0.80	0.534304	0.527143	0.744131
1783	283000.0	0.80	0.534304	0.527143	0.744131
1784	284000.0	0.80	0.534304	0.527143	0.744131
1785	285000.0	0.80	0.534304	0.527143	0.744131
1786	286000.0	0.80	0.534304	0.527143	0.744131
1787	287000.0	0.80	0.534304	0.527143	0.744131
1788	288000.0	0.80	0.534304	0.527143	0.744131
1789	289000.0	0.80	0.534304	0.527143	0.744131
1790	290000.0	0.80	0.534304	0.527143	0.744131
1791	291000.0	0.80	0.534304	0.527143	0.744131
1792	292000.0	0.80	0.534304	0.527143	0.744131
1793	293000.0	0.80	0.534304	0.527143	0.744131
1794	294000.0	0.80	0.534304	0.527143	0.744131
1795	295000.0	0.80	0.534304	0.527143	0.744131
1796	296000.0	0.80	0.534304	0.527143	0.744131
1797	297000.0	0.80	0.534304	0.527143	0.744131
1798	298000.0	0.80	0.534304	0.527143	0.744131
1799	299000.0	0.80	0.534304	0.527143	0.744131

	Cost_test	Accuracy
Alpha
0.01	0.534349	0.745144
0.05	0.534304	0.745144
0.08	0.534304	0.745144
0.10	0.534304	0.745144
0.50	0.534304	0.745144
0.80	0.534304	0.745144

	Cost_test	Iteration
Alpha
0.001	2587.221676	1827.0
0.003	2584.741194	703.0
0.005	2584.140672	449.0
0.010	2583.604498	244.0
0.050	2582.918373	62.0
0.500	2526.843029	2015.0
1.000	2501.896423	3137.0

	Cost_test	Iteration	Convergence_criteria
Convergence_criteria
0.001	2365.316088	69396.0	0.001
0.005	2479.727427	7013.0	0.005
0.010	2501.896423	3137.0	0.010
0.050	2525.475706	1341.0	0.050
0.100	2537.051837	1150.0	0.100
0.500	2622.033816	772.0	0.500

	Iteration	Alpha	Cost_test	Cost_train	Accuracy
0	0.0	0.5	0.693147	0.693147	0.463266
1	1000.0	0.5	0.584487	0.589623	0.691099
2	2000.0	0.5	0.584488	0.589623	0.691099
3	3000.0	0.5	0.584488	0.589623	0.691099
4	4000.0	0.5	0.584488	0.589623	0.691099
5	5000.0	0.5	0.584488	0.589623	0.691099
6	6000.0	0.5	0.584488	0.589623	0.691099
7	7000.0	0.5	0.584488	0.589623	0.691099
8	8000.0	0.5	0.584488	0.589623	0.691099
9	9000.0	0.5	0.584488	0.589623	0.691099
10	10000.0	0.5	0.584488	0.589623	0.691099
11	11000.0	0.5	0.584488	0.589623	0.691099
12	12000.0	0.5	0.584488	0.589623	0.691099
13	13000.0	0.5	0.584488	0.589623	0.691099
14	14000.0	0.5	0.584488	0.589623	0.691099
15	15000.0	0.5	0.584488	0.589623	0.691099
16	16000.0	0.5	0.584488	0.589623	0.691099
17	17000.0	0.5	0.584488	0.589623	0.691099
18	18000.0	0.5	0.584488	0.589623	0.691099
19	19000.0	0.5	0.584488	0.589623	0.691099
20	20000.0	0.5	0.584488	0.589623	0.691099
21	21000.0	0.5	0.584488	0.589623	0.691099
22	22000.0	0.5	0.584488	0.589623	0.691099
23	23000.0	0.5	0.584488	0.589623	0.691099
24	24000.0	0.5	0.584488	0.589623	0.691099
25	25000.0	0.5	0.584488	0.589623	0.691099
26	26000.0	0.5	0.584488	0.589623	0.691099
27	27000.0	0.5	0.584488	0.589623	0.691099
28	28000.0	0.5	0.584488	0.589623	0.691099
29	29000.0	0.5	0.584488	0.589623	0.691099
...	...	...	...	...	...
270	270000.0	0.5	0.584488	0.589623	0.691099
271	271000.0	0.5	0.584488	0.589623	0.691099
272	272000.0	0.5	0.584488	0.589623	0.691099
273	273000.0	0.5	0.584488	0.589623	0.691099
274	274000.0	0.5	0.584488	0.589623	0.691099
275	275000.0	0.5	0.584488	0.589623	0.691099
276	276000.0	0.5	0.584488	0.589623	0.691099
277	277000.0	0.5	0.584488	0.589623	0.691099
278	278000.0	0.5	0.584488	0.589623	0.691099